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Exploring Possibilities for AI and ML for Drug Discovery  

Developing new medicines is not for the faint-hearted! On average, it takes about a decade of research with an expenditure that amasses US$2.6 billion to Out of the total drug discovery done only about 5 per cent of experimental drugs make it to market! This paves way for drug makers and pharma companies to invest hugely in artificial intelligence and machine learning with the hope that these technologies will make the

Machine Learning Applications at Biopharma Companies

The high prices of the drugs are attributed to the significant costs of drug research and development, done by the pharma giants. This figure has recently been estimated to average around UD$2.6 billion per treatment. It takes up to 15 years to bring a new therapy to market. Less than 12% of drugs that enter clinical trials end up being commercialized, leading to pharma’s and investors turning their gaze to making drug discovery a faster process in the recent times especially post Covid-19 aftermath. Artificial Intelligence (AI) has recently been earmarked as a debated topic of interest in the area of

Fostering Global Pharma Alliances

Several prominent AI and ML companies bog and small have focused some of their resources to address the inefficiencies of this space-

Developing new medicines is not for the faint-hearted! On average, it takes about a decade of research with an expenditure that amasses US$2.6 billion to shepherd an experimental drug from lab to market . The field of artificial intelligence and machine learning (AI/ ML) has witnessed sharp upturns, particularly concerning deep learning (DL) methods that are pillared with the availability of big data. Biomedical data is humongous and becoming increasingly available in ML-ready digital formats, it is now possible to deploy AI/ML algorithms to support h ealthcare research and services . However, within the larger healthcare ecosystem, biopharmaceutical companies, in particular, have been criticized for the skyrocket pricing of prescription drugs. Artificial Intelligence and Machine learning have the power to improve drug discovery and medical research which may reduce drug prices in the chúng tôi paves way for drug makers and pharma companies to invest hugely in artificial intelligence and machine learning with the hope that these technologies will make the drug discovery process faster and chúng tôi high prices of the drugs are attributed to the significant costs of drug research and development, done by the pharma giants. This figure has recently been estimated to average around UD$2.6 billion per treatment. It takes up to 15 years to bring a new therapy to market. Less than 12% of drugs that enter clinical trials end up being commercialized, leading to pharma’s and investors turning their gaze to making drug discovery a faster process in the recent times especially post Covid-19 aftermath. Artificial Intelligence (AI) has recently been earmarked as a debated topic of interest in the area of medical care . Biopharmaceutical industries are putting their efforts to expand their viewpoint in AI to enhance the drug discovery process, diminish failure rates in clinical trials, generate superior medicines and reduce research and development expenses. Accessibility of methodological statistics in life sciences coupled with speedy developments in machine learning algorithms has led to an evolution of AI-based start-up companies focused on drug discovery over the recent years.Several prominent AI and ML companies bog and small have focused some of their resources to address the inefficiencies of this space- • Pfizer , has partnered with IBM Watson to identify more robust targets during the discovery phase, process thousands of scientific publications to determine novel combinations of drugs for improved efficacy, and optimize the patient selection for clinical trials. • Insilico Medicine and Exscientia , are attempting to utilize genomics and artificial intelligence tools for computational design of new drug candidates. If the integration of AI into the drug discovery and design process works, it can have incredible disruptive effects. It could disrupt the entire drug discovery ecosystem throwing many chemoinformatics out of jobs. However, cutting down drug discovery from years to months especially after Covid-19 pandemic would mean an incalculable effect on the larger pharma environment. An industry which justifies its high drug prices by the lengthy and costly research undertaken at the development phase, it ‘ll be a tectonic shift, that seems like a gamble worth taking.

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Top 10 Ai Tools For Academic Research

Following is a list of the top 10 AI tools for academic research helpful for researchers

Scholars and Students have devoted countless hours to academic research and writing throughout history. Even though researchers now have access to more information and AI tools than ever before thanks to technology and the internet, it can be challenging to find the right AI tools for research.

Scholars and researchers require assistance sorting through and organizing sources due to the abundance of information available today. In addition, scholars and researchers must write informative, engaging, and well-written articles and reports due to the ongoing pressure to publish. Here is the list of AI tools for academic research.

1. Consensus: 2. ChatPDF:

Users can converse with a PDF document through the AI application ChatPDF. Without signing in, users can interact with any PDF they own, such as books, research papers, manuals, articles, and legal documents. To comprehend the content of PDF files and provide pertinent responses, ChatPDF makes use of a next-generation AI model comparable to ChatGPT.

3. Scite:

Scite’s Assistant, an AI-powered research tool, lets users work together on essays and research papers, find evidence to back up their claims and find evidence to refute them. Clients might enter straightforward questions to get reactions in light of the total texts of exploration distributions. The application can be used by users to find reliable information, search through millions of research articles, and create grant proposals or essay drafts.

4. Elicit:

Elicit, a machine learning tool, is used by the AI research assistant to help automate research procedures. Without specific keyword matches, it can locate relevant articles and extract important information. Inspire may likewise give different exploration exercises, including conceptualizing, summing up, and text-order, as well as summing up central issues from the report that are pertinent to the client’s request.

5. Trinka:

Online sentence structure checker and language proofreader Trinka artificial intelligence was made for specialized and scholastic composition. It is made to catch errors that other grammar checkers miss, like issues with subject-verb agreement, syntax, word choices, the use of pronouns and articles, and technical spelling. In addition, it incorporates a professional tone, the use of technical words, conciseness that goes beyond grammar and spelling, and style guides.

6. Scholarcy:

The online summarizing tool Scholarcy is a simple way to quickly examine and evaluate the significance of documents like articles, reports, and book chapters. Any Word or PDF document can be used to create summary flashcards that are displayed in an organized and easy-to-understand manner.

7. Academic Semantics:

The vast majority know about Google Researcher, which uses Google’s web search tool ability to list academic distributions. But if you’re doing any kind of scientific research, you should try Semantic Scholar. This AI-powered search and discovery tool, made available by publisher partnerships, data suppliers, and web crawls, enables you to keep up with more than 200 million academic publications.


Utilizing the internet to find information is a blessing. The amount of data that is accessible and the fact that it can be found in a variety of formats, such as blogs, essays, films, infographics, and images, present two challenges. Finding and organizing all of the data related to your study’s many areas might take a lot of effort.

9. SciSpace:

SciSpace is a platform driven by AI that lets people read, understand, and submit scientific articles. Its extensive searchable database contains more than 270 million articles, authors, subjects, journals, and conferences. It also offers a variety of paper template choices, a variety of pricing options, and additional services to speed up the printing process.

10. OpenRead:

Research Ethics: Meaning And Application

Research is an ongoing, exacting process. In fields like the humanities, social sciences, biology, and medicine, the researcher and the subject of their study are in close contact. The science of humanity as a whole is called anthropology. The researcher and the researcher (interviewer-interviewee, scientist-subject) share ecosystems, histories, and occasionally ethnic and linguistic identities in most fields of the discipline. Researchers frequently hold positions of authority in the area, which increases the likelihood that they may project their preconceptions and stigmas onto the individuals they encounter with.

Research Ethics Meaning

The Nuremberg trials, which took place in 1945–1946 and saw the prosecution of numerous Nazi scientists who had done cruel experiments on disabled people, homosexuals, and other persecuted groups, contributed to the development of the area of research ethics. The world was appalled when these scientists’ cruel tactics were revealed. This demonstrated the lengths scholars would go to in their ostensible quest for knowledge—torture. This served as a wake-up call to the scientific community, highlighting the necessity of establishing ethical guidelines that researchers must abide by when conducting their study.

The Nuremberg Code (1947), which established the guidelines for human testing, contained these regulations. Its fundamental tenet is that no human subject may be subjected to an experiment without that subject’s agreement. Any study participant should not suffer any injury during an experiment that has the potential to cause them harm or even death. Any associated risk with a study is only acceptable because the predicted rewards from the investigation offset it. All other factors are superseded by the study subject’s safety and consent.

All the following ethical principles and regulations for research ethics are founded on the Nuremberg Code. Many professional groups and research councils worldwide, including India, have embraced several of these standards. The Ethical Guidelines for Biomedical Research on Human Participants (2006), published by the Indian Council of Medical Research, and the Ethics Guidelines for Social Science Research in Health (2000), published by the National Committee for Social Science Research in Health are two important ethical guidelines for research in India.

Theoretical Approach

There are two theoretical perspectives to comprehend ethics and its application to social sciences. Theoretically, consequentialism or utilitarianism holds that an action’s morality or immorality may be determined by its repercussions. As long as the goal is achieved, any forms of experimentation and inquiry are legitimate. According to this viewpoint, it is OK to test novel medications or treatments on humans without understanding how they would affect their bodies.

They contend that if it benefits “experimental participants,” it will also assist millions of other people. However, if “subjects” suffer or even pass away during the trial, it is determined that the experiment must be stopped, saving millions in both financial and human costs. This philosophical approach’s ethics are based on cost-benefit calculations.

Human experimentation is any experiment performed on a living individual, not for therapeutic purposes but to learn how it would affect him. Examples include administering growth hormones to young children to observe the effects, administering low doses of insulin to healthy individuals as a control group, administering trial medications to patients to determine their potential for healing, administering electric shocks to individuals to gauge their capacity for endurance, etc. Several instances of “live ethics in research human subjects” being treated inhumanely during social and medical research.

The most notorious instance is that of Nazi Germany when war captives were put through cruel examinations and torture in the name of medical research. These included “incompatible unsterile blood transfusions, (e.g., giving Rh positive or Rh negative blood to an Rh-positive individual, or giving blood from blood type A to inmates, etc.)” injections of harmful chemicals, forced sterilization of women because they are mentally ill and would likely produce mentally ill offspring disrupting the population’s gene pool, and performing surgeries without anesthesia. Holocaust survivors and others subjected to these experiments had psychological effects for the rest of their lives. This emphasized the necessity of voluntary involvement and informed consent in all types of study.

Principles of Research Ethics

Some of the principles that are crucial to conducting ethical research are −

Honesty − Honesty ensures that the researchers truthfully share crucial details of the study with respondents, colleagues, and authorities.

Objectivity − This principle helps avoid any biases influencing the study.

Integrity − Integrity helps to maintain consistency of actions throughout the conduction of the study.

Carefulness − Carefulness helps avoid any errors committed during the study and rectify the errors made.

Openness − This principle ensures that the researcher is open to criticism and new ideas that may help improve the study.

Transparency − This principle helps ensure that all necessary information is accurately disclosed to evaluate the research adequately.

Accountability − Accountability ensures that the researcher holds responsibility regarding all concerns of the study.

Originality − This principle helps ensure that the study is free from plagiarism and that proper credits are given to the sources used in the study.

Confidentiality − This principle helps to ensure that all sensitive information is safeguarded and the participants’ responses stay only with the researcher.

Protecting of rights − This principle helps protect the rights of humans and ensures that no animal is harmed during the conduction of the study.

Legal Consideration − This principle helps researchers ensure that all legalities are followed during the study.

Each research participant must be made aware of the following by the researcher −

The purpose of the study.

The participants have free will to participate in the study.

The respondents can withdraw from the study at any point.

The possible benefits and risks involved in the study.

Confidentiality of the study will be maintained.

Ethical Failure in Research

Ethical failure occurs when participants are mistreated by the researcher or their rights or dignity are violated during the conduction of the study. Research misconduct is another ethical failure in which the researcher falsifies data, manipulates the results, misinterprets the results, or commits academic fraud. Such actions are carried out intentionally and may waste the resources and funding involved in the study. Another type of ethical failure is plagiarism, which indicates that the study is not original and that someone else’s work is copied, either intentionally or unintentionally. Ethical failure also occurs when harm is caused to the participants.

Psychological harm is caused when triggering questions are asked, causing anxiety or shame.

Social harm involves social stigma, stereotypes, public embarrassment, and social risks.

Physical harm occurs when any injury is caused during the research conduction.

Legal harm is caused to respondents when privacy is breached or the confidentiality of participants is not maintained.

Application of Principles of Ethics

Assessment − Identifying the research problems effectively, chalking out the goals of the study

Voluntary Participation − Not forcing individuals to become a part of the study and letting them become a part of the research by their will.

Rights of the participant − The participants should be told that they can choose not to share particular information and choose to withdraw from the study at any given point.

Beneficence − Ensuring that the benefit of the participants is maximized.

Confidentiality − The privacy and anonymity of the participants should be maintained.

Non-discrimination −  Avoiding participants’ discrimination on race, religion, sex, and creed.

Advantages of Research Ethics

Research ethics increase the trust between researchers and the respondents.

Ethical principles help protect the respondents’ rights, welfare, and dignity.

The respondents can hold researchers accountable for answers.

Research helps in promoting social as well as moral values.

Research ethics help avoid errors, publish original research and veracity, and better understand the study.

Ethical values adopted in research help increase cooperation, answerability, impartiality, and mutual respect.

Respondents are likely to trust the researcher, and the research study follows ethics and increases the trust and reliability of the study.

Limitations of Research Ethics

Research involving experimental drugs or equipment such as x-ray machines can cause physical harm to the participants.

Some research can cause psychological harm to individuals as some questions may trigger anxiety and bring back memories of certain traumatic events.

Tribal or other backward groups may face stigmatization and discrimination during the study.

The data collected may be released unintentionally, violating the rights and confidentiality of the participants.

How can studies be made ethical?

The following steps can be followed to make a research ethical −

Collect accurate facts.

Map out the ethical concerns.

Respondents should recognize their responsibilities.

Respecting the privacy and confidentiality of participants.

Resolving the ethical issues once recognized.


Principles of ethics are essential to be followed by researchers to ensure that fair research is conducted, which is free from plagiarism, and the rights of respondents are not violated. Ethical research does not violate legal norms and ensures that no harm is caused to the respondents intentionally or unintentionally.

Career In Learning And Development

Overview of Career in Learning and Development

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The current decade of digital disruption, rising of artificial intelligence, and the gig economy intensifies the need for developing a workforce with the right skill and knowledge to stay prevalent in the rapid transformation of the business environment in the corporate sector of India. According to a recent survey report, most of the organization’s Learning Development Index (LDI) is below the expectation level. That is why some organizations attempt to implement the alignment of employee development strategy with business strategy. In these current years, the demand for learning and development personnel has been increased for developing knowledge levels of employees across various industries, and swiftly it turns out to be a lucrative career opportunity.

The Forthcoming Industries for L&D Professionals

Though L&D professionals have mostly aspired in the HR and sales industries, yet all types of industries prefer to hire them. After all, a knowledgeable workforce is the backbone of the growth of any industry. The industries that recruit L&D professionals are as follows –

Health care

Educational services

Financial and insurance

Scientific and technical services

Retail companies

Central and Local Government

Law firms

Manufacturing organizations

Training consultancies

Different Roles for L&D Professionals

The professionals can choose this career path at any stage of their career. It provides a wide range of opportunities both at the junior and senior levels. Some common L&D roles are as follows–

L&D Advisor

L&D Manager

Head of L&D

Training Project Administrator

Talent Acquisition Consultant

Sales Trainer

The Career Stance and Salary structure

As Indian companies are expanding their businesses globally, it becomes essential to increase the investment in L&D to enhance the skill level of employees at per global standard, though India’s investment in L&D is less compared to the developed countries. TCS, Cognizant, Infosys Limited, Maruti Suzuki India Limited, Hindustan Aeronautics Limited, etc. They also provide an environment of continuous learning for its employees. Till 2023, the average salary of a Learning and Development professional was Rs. 914,951 in India, and the salary structure may be changed and increased on the basis of experience.

Required Qualification to Pursue L&D Profession

All professionals in the L&D field have a college degree, while some have acquired master degree qualification also. But recent survey report shows that many professionals have graduation or post-graduation degrees in human resources, law, social science, education, and psychology. As technology plays a crucial role in the learning and development field, the candidates of computer science or information technology are also considered to recruit in this field by different industries. Besides qualification, a professional must have some essential skills and personal traits to establish him or herself in this field.

The Requisite Skills Career in Learning and Development

Interpersonal Skills: The trainer must have good interpersonal skills to make the training program interesting and effective. It is recommended to have good listening skills to realize the audience’s requirements. If the trainer has to improve the quality of social perception, which helps to empathize with others’ reactions and can adjust messages and approach accordingly. The professionals in the L&D field have to develop a constructive working relationship with others rather than working as a consultant in their organization.

Communication and Motivational Skills: The professionals who have decided to enter the L&D field must develop excellent oral and written communication skills. Because as a trainer, he or she may address a large or small group of people and write effectively for a large group of viewers. With giving training for skill or knowledge development, the trainer has to motivate the audiences with inspirational speech or story sharing as well as game playing.

Initiative and Creativity: L&D professionals think creatively to design new programs and approaches for communicating information effectively to the trainees. That is why they need to take the initiative for the implementation of a new design or approach.

Planning: The L&D professionals have to be capable to chalk out detailed plans for an effective training program and collect materials accordingly.

Technology Skill: It is important that L&D professionals must have technological skills. As a trainer, he or she should have knowledge about the operating of technology in the classroom as well as effective use of the learning management system and online meeting platform.

Apart from that, a professional must develop some personal qualities to become a successful trainer.

Personal Qualities: Career in Learning and Development

Extrovert: Most of the training professionals are extroverts than introverts as they engage with training delivery. But introverted persons also become successful trainers if they choose to teach a small group of people or to use an online platform for providing training.

Flexibility and Problem Solving Skill: As trainers do their own planning and pay attention to detail, they must have to think on their feet and quickly adjust to any unwanted situation. This Learning and Development field has so much diversity that all types of personal traits can get the opportunity.

Time Management: The trainer designs the entire training program within an estimated time frame, and he or she should not deviate from the time schedule.

There are a lot of opportunities in the L&D field, but jobs are unfilled because of the lack of skillful workers. Even the organizations should enhance their training function by investing time and budget to upskill the training team. This investment will help the training team to traverse the challenges of today’s business environment to deliver world-class training.

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This has been a guide to a Career in Learning and Development. Here we have discussed the different roles, career and salary structures, qualifications, and skills of L&D professionals. You can also go through our other suggested articles to learn more –

The Rise Of Remote Work And How Can Increase And Development

COVID-19 has accelerated the rate of remote work adoption globally, but what have we found out? We have discovered that remote work is not bad, after all.

Before, many businesses have been cautious about transitioning to telecommuting, even if many of the office surgeries do not need the physical presence of workers. The main concerns expressed by leaders incorporate a potential decrease in worker productivity and also a lack of clarity concerning the measurement of worker performance.

The operation of individual workers determines the trajectory of the provider. Without reliable procedures to estimate its workers’ work, it’s hard for any company to achieve development and growth.

This report addresses the concerns of supervisors that are reluctant about distant work and people who have implemented distant work but have difficulty with monitoring performance for office productivity and workplace development.

Set Clear Objectives and KPIs

Communication to employees that the ways by which their performance will be evaluated assists them to understand their own priorities. Clear expectations, keep workers focused.

Acknowledge Unquantifiable Performance Indicators

In placing KPIs, however, you want to admit that numbers do not tell the complete story. Not to imply that you ought to dismiss the value of amounts, but you need to also be mindful of the major Intangible Performance Indicators. Ironically, working remotely can compound the vagueness of these indexes — causing workers to feel that their efforts aren’t recognized enough.

Some facets are simply not quantifiable, such as leadership, creativity, invention, business, and participation. You can find quantifiable indicators that will make us comprehend employee participation and business, but the topics themselves are indefinite.

Until fresh approaches and means of quantifying these intangibles are found — firm leadership must admit that Key Intangible Performance Indicators exist, and search for ways to recognize employees who go above and beyond.

Support Employee Development

Assessments needs to be more supportive than they’re judgmental. Employees love frequent check-ins once the purpose is to keep them on their feet and encourage them through issues. On the other hand, the supervisor which goes around always pointing his group members’ defects (without thoughtfully helping them conquer their struggles ) is just regarded as grumpy.

The rules also apply in distant work, in which supervisors (from fear of losing control) start acting intrusively by executing intense company surveillance. Tracking and evaluation are not the endings; The objective of monitoring employee performance ought to be to boost team productivity. Essentially, remote workforce management and functionality needs to usher us into a new era of confidence, more freedom, responsibility, and staff cooperation.

Nowadays, it is not enough to equip teams with new digital tools for remote collaboration, which many rapidly did when the pandemic began. It’s only the first step,” says Maxime Bouroumeau-Fuseau, co-founder and CTO of Paris-based Digicoop, a worker cooperative behind the work management platform Kantree. “The changing workplace calls for an environment where employees are empowered to take control of their work.

In our expertise for a co-op, when workers are given more freedom and if micromanagement is substituted by cooperation, teams deliver greater outcomes while human workers feel more invested in their job.”

Allow Autonomy

A lot of people decide to work remotely because they wish to feel a better sense of ownership of the schedules and time. Therefore, although time monitoring is essential for many distant groups, it goes without mentioning that hourly input isn’t always a fantastic measure of functionality.

The real measure of operation is the job result. Remote work enables employees to pick their own work hourswhat does it matter if an employee works less a hour but nevertheless meets goals consistently? Scientists have revealed that freedom increases productivity.

Use the Right Tools and Analytics

With physical offices from the picture, it’s the tools that a distant team uses that specify the arrangement of operations and work. You will find tools that keep workers accountable and supply actionable insights to how work gets done inside the business.

The growth of distant work has boosted the value of analytics of routine work information to make sure that workers are more successful.

Establish a Culture of Accountability

Notice, however, that resources are just as powerful as the civilization in which they’re situated. Your staff may use the very best tools, but bad communication can derail workers from the key aims of the provider.

Whenever there are issues with worker operation, you ought to have the ability to recognize whether there’s a issue with the tools being used or together with the direction. Accountability shouldn’t be down-up; it needs to be top notch too. Managers ought to be answerable to their own customers and transparent about office deals.


Going by data , remote function really enhances employee productivity and functionality. This, then, contributes to the total development of the corporation. But this expansion has to be intentional. Organizations should employ proper (and adaptive ) evaluation models to understand when their job is actually progressing and if there are issues that have to be solved.

Ai Vs. Coronavirus: Impact Of Coronavirus On Us And Technology

The world is becoming a technology crystal ball. The internet is bound to everything, including our homes, schools and workplaces. It also connects us all to the restaurants we love to eat every weekend.

Artificial Intelligence (AI), the Internet of Things, and other technologies allow us to see smart tools and automation technologies almost every day. AI facilitates us at home, and it also helps healthcare workers do their jobs.

Smart devices were installed in ambulances and hospitals, and healthcare workers used these technologies.

Technology Needs to Peak With COVID

The pandemic struck us hard. These technologies were needed most acutely during the coronavirus. Frontline workers must be able to assist patients without compromising their social isolation or health.

By default, AI is the top choice. AI can be used to select better vaccine options, but IoT, specifically the Internet of Medical Things, offers better ways to aid and treat patients.

We are currently studying the impact of COVID-19 and how AI and IoT can facilitate the healthcare industry.

You can also see Artificial Intelligence is Neutral Technology: How Social Media Can Help Healthcare

The impact of Coronavirus on us, technology

Coronavirus was a complete stop in an ever-changing world. It took millions of lives worldwide, but it also opened the door to new healthcare technologies.

COVID established a new standard of social distancing and gadgets were created to assist authorities in monitoring it. Corona Virus brought to light the controversy surrounding anti-maskers.

Every store has a different opinion on the freedom to not wear a mask when customers are anti-masker. AI and computer vision are now able to create devices that can stop anti-masker customers without arguing. AI allowed us to have digital access, even though we were unable to access the rest of the world due to the pandemic.

Broad Reach of COVIDs

This novel virus had a lasting impact on every corner. It also brought about a new technology. These technologies were indirectly used to help the healthcare industry combat the coronavirus. These technologies do not only provide indirect assistance.

We are now open to the possibility that other pandemics could occur in the future. It also set us on a path that allowed us to use technology in healthcare more often than ever before. AI is used by healthcare workers and hospitals to diagnose a disease or administer dosages.

Technology is affecting COVID-19, but it can also be the reverse.

AI helps to fight Coronavirus

AI and IoT have proven to be intelligent solutions to the pandemic since the beginning of COVID-19.

AI aids frontliner in combating coronavirus by introducing new devices and using existing inventions. Many researchers also came up with innovative solutions to combat COVID.

Healthcare uses a variety of AI-powered devices and solutions to monitor, diagnose, and treat patients. They also transport aid, enable social distancing, provide financial services, and can even be used for diagnosis and treatment.

Six examples of AI’s many applications are shown below. They are helping healthcare workers fight COVID-19.

1. Social Distancing Solutions

Despite the huge death toll from the coronavirus, there are still people who don’t follow social distancing guidelines. Although it may not seem like an issue for healthcare workers but the increase in COVID cases is a result of social distancing laws being broken. This is why managing this issue is an important weapon in the fight against COVID-19.

Also read: 5 Best Resource Capacity Planning Tools for Teams

2. Automated Initial Test

Healthcare workers can benefit from IoT by automating initial COVID testing. Researchers have been working hard to find ways to speed up test results since the beginning of the pandemic. There are many automated tests available, including predictive pathology and lung scan testing.

These AI solutions can quickly test for COVID and reduce the chance of healthcare workers contracting the disease. This technology allows healthcare professionals around the world to test COVID faster and with fewer cases, without putting lives at risk.

3. Fast Diagnosis and Safer Treatment

Also read: Top 5 Automation Tools to Streamline Workflows for Busy IT Teams

4. Automation in the Medicine Supply Chain

The healthcare industry also faces the challenge of managing its supplies manually. COVID-19 caused a shortage of medical equipment due to an increase in its use. There was no global monitoring of the supply of medical equipment.

Black-market looters were also a problem. IoT/AI once more proved to be the best solution as automation became a necessity in supply and supply chain management. Predictive analytics and optimization of healthcare supply chain costs gave control over existing equipment and enabled the healthcare industry to automate the ordering process.

5. AI to Vaccine Solutions

AI goes beyond automation. It can be used in nearly every field of prediction. AI offers pioneering solutions for predictive analysis, including the ability to predict weather and human behavior. It can be used in the same way that AI is used to predict people’s behavior via social media.

AI-based predictive analytics can be used to create and perfect vaccines not only for COVID-19, but also for any future pandemic. This requires years of research but can lead to a path for treatment of a large number of diseases.

6. Predicting and Governing Virus Status

Also read: The 15 Best E-Commerce Marketing Tools


COVID-19 had a major impact on our lives but also gave us the ability to be proactive and ready for similar problems in the future. We have made our tools and technologies compatible with these issues and are now able to adapt to them. Just as COVID has an impact on technologies, IoT and AI are helping to fight this pandemic.

COVID-19 has imposed many challenges on the healthcare industry. But it is not just the healthcare industry that must face them. Everything was affected by the pandemic, from education to businesses. Similar to AI and IoT helping healthcare, AI and IoT also help other fields.

AI-based solutions form the foundation and part of almost every future technology. Algoscale assists industries in incorporating these AI solutions into their business models. Algoscale provides AI solutions for startups and enterprises, from prediction to automation.

We hope you found this article useful. Algoscale strives to provide you with knowledge on a wide range of subjects. Keep reading to learn more and keep up-to-date. Happy Learning!

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