AI in Healthcare

The AI Revolution in Healthcare

The face of healthcare is being transformed with revolutionary advancements in the field of AI. The deep learning technology is adroitly addressing crucial aspects of patient care as well as internal administrative procedures for healthcare-related organizations. In fact, healthcare systems are becoming faster, smarter, and more efficient by leveraging artificial intelligence-based technologies.

Several studies have shown that AI for healthcare is capable of facilitating accurate disease diagnosis, effective treatment, and curated care for patients better than humans in most cases. Today, algorithms already surpass radiologists in identifying malignant diseases such as cancerous tumors or heart conditions even before they occur. Deep learning is being used in clinical settings for informed decision-making, saving time and costs for both healthcare providers and beneficiaries. Professionals also use AI to perform several tasks, from listening to health records using text to speech to using surgical robots for precision in surgeries. 

Although it will be a while before AI completely replaces humans in the healthcare sector, it has already become indispensable for medical providers. This article will discuss at length how AI is used in the healthcare industry, its advantages, challenges, and some top AI tools that are changing the way we do healthcare. 

Types of AI in Healthcare

AI technologies, such as traditional machine learning, deep learning, and natural language processing, are helping simplify healthcare procedures and improve health outcomes. In this paragraph, we will provide detailed info on some of the main types of AI being used in healthcare, each with its own unique capabilities and applications. 

Machine Learning

Machine learning is used extensively in the healthcare sector for accurate diagnosis, personalized treatment, and timely prevention of medical conditions. Precision medicine—predicting what treatments will be effective for the patients—is another primary application of machine learning technology in healthcare. 

Natural Language Processing

Natural language processing is leveraged in the medical industry for text analysis, speech recognition, and translation. Natural language processing can easily facilitate conversational AI through chatbots, create medical reports from patient data, analyze clinical documentation for patients, and transcribe conversations. 

Rule-Based Expert Systems

Rule-based expert systems are used to make several diagnoses and treatment-related decisions, including managing abdominal aneurysms. The specialized rule-based systems input the diameter of an aneurysm and, by using conditional arguments, recommend whether immediate intervention is required. If not, appropriate follow-up is recommended.

Diagnosis and Treatment Applications 

The diagnostic findings and precision medicine suggestions are usually based on—but are not limited to—radiological analysis of images, retinal scanning, and genomic-based precision medicine. Researchers use 'population health' machine learning models to predict populations at high risk of certain infections or diseases. AI in electronic health record systems facilitates the use of big data to generate personalized treatment recommendations, improving patient outcomes.

Administrative Applications 

The wide-ranging administrative applications of AI in healthcare industry include but are not limited to claims processing assistance, clinical documentation creation, and medical records management. In daily clinical practice, healthcare organizations now use AI chatbots for 24×7 patient interaction, mental health wellness, and telehealth support. Text to speech software are also helping medical providers create medical training materials and convert complex documentation into interactive media, schedule personalized outbound calls with patients for appointment reminders, and guide patients during self-performed minor procedures.

Physical Robots

Surgical robots are another type of artificial intelligence being used for minimally invasive surgeries due to their ability to manipulate surgical instruments beyond human capability in a relatively smaller operation space. They provide many benefits, including enhanced accuracy, precision, dexterity, tremor control, and scaled motion. These robots also assist with manual tasks such as heavy lifting, equipment repair, deliveries, and people management. 

Robotic Process Automation 

Robotic Process Automation (RPA) facilitates efficient and accurate medical data management by ensuring electronic data sharing adheres to privacy protocols. The technology assists by scanning incoming data and setting up appointments based on relevant data such as doctor availability, most convenient time, location, symptoms, or suspected diagnosis. Healthcare organizations also use it to streamline the settlement of health payments by combining various costs into simplified payments. These costs include doctor fees, tests, medicines, and food.

Benefits of AI in Healthcare

Artificial intelligence offers a plethora of benefits for not only healthcare providers but also its beneficiaries. From early disease detection to personalized treatment plans, AI and data science are transforming healthcare in unprecedented ways.


Artificial intelligence technology increases health equity. In other words, it makes healthcare more accessible to patients from all income groups by saving time, cutting costs, and improving the overall convalescence journey of the patient. AI also enhances the access medical professionals have to their patients by streamlining clinical and administrative processes such as appointment scheduling and personal prescription making. 

Early Diagnosis

Since early signs of disease are not often evident in laboratory test results, predictive models that leverage artificial intelligence, or neural networks in particular, can help identify areas of concern, even before any noticeable physical symptoms appear. This allows the healthcare specialist to take the necessary preventive measures to curtail the potential danger in an informed manner.

Reduce Costs

By employing AI for medical diagnosis, treatment, surgical procedures, research, and administrative tasks, hospitals and clinical organizations can significantly reduce the costs of professional human interventions such as data managers or wardens. Similarly, improved accessibility of advanced healthcare through AI cuts expenses for patients at the same time. 

Assistance in Surgery

Artificial intelligence-based systems can be fed recordings of thousands of surgeries for it to learn every procedure with the same precision. Apart from skillfully performing minimally invasive surgeries, AI-based systems can guide surgical procedures and ensure a more streamlined process by highlighting tools, monitoring operations, and sending alerts. 


One of the benefits of adopting AI is that it can finish clinical processes that previously required extensive manual labor much faster. This allows the staff, such as medical data managers and nurses of hospitals and other healthcare organizations, to focus on other high-priority matters. Using deep learning models can significantly improve the efficiency of healthcare executives by saving ample amounts of labor, time, and money. 

Drug Creation 

AI in healthcare is revolutionizing diverse pharmaceutical industry sectors, including drug discovery and creation, drug repurposing, and drug clinical trials. AI can deliver value in small-molecule drug discovery in four ways: providing access to new biology, facilitating improved or novel chemistry, yielding better success rates, and using quicker and cheaper discovery processes.

Challenges for Artificial Intelligence in Healthcare

Despite the wide-ranging benefits, there are several challenges faced during artificial intelligence's implementation, which prove to be a barrier. Let's explore some of the challenges of AI in healthcare.

Ethical Implications

It should be highlighted that one faces several issues when employing AI in healthcare. Several low-income and developing nations continue to lack access to AI while the urban sectors reap its benefits. However, concerns surrounding the handling of sensitive medical data and maintaining privacy can be challenging for professionals. AI healthcare systems can also be prone to bias and discrimination based on training datasets, which can lead to the mistreatment of healthcare payers based on race or gender.

Implications for Workforce in Healthcare

Certain tasks that have traditionally been done by humans, such as report creation, have been automated by AI in healthcare, putting at risk the jobs of skilled staff. There are also concerns that introducing AI systems might leave less-skilled staff under-prepared in the absence of AI.

Privacy Concern

Privacy is a major concern while using artificial intelligence in the healthcare sector. Patient data includes sensitive, personally identified information (PII) like medical history, identity information, and financial information. This raises the risk of data leaks, breaches, and personal information being exposed or used maliciously.


AI algorithms are only as unbiased as the data used to train them, and if the data is biased, the algorithm will be too. This could lead to inaccurate diagnoses or treatment recommendations, particularly for underrepresented patient groups, which could lead to severe repercussions for healthcare payers. 

Top Five AI Tools Used in Healthcare 

Here are the top five AI tools that are revolutionizing the healthcare sector and producing better health outcomes worldwide: 


Merative (formerly IBM Watson Health) offers a suite of products and services for clinical decision support, clinical development, enterprise imaging, healthcare analytics, social program management, and more. Its solutions, Micromedex and DynaMedex, are evidence-based clinical decision support systems that provide detailed drug and disease information which is updated daily. Merative's health data management and acquisition platform, Zelta can execute research, manage participants, route tasks, and report results to stakeholders during clinical trials. Moreover, its Merge imaging solutions can meet all the radiology, cardiology, and all other imaging needs by simplifying imaging workflows with modern user interfaces, quick insights delivered by AI, and single-point access to full patient records.


PathAI is a healthcare business that creates reliable and adaptable AI-based pathology solutions with extensive computational and medical knowledge. These solutions hasten drug discovery, boost patient confidence with the accuracy of diagnoses, and expedite the delivery of life-saving treatments. One of its solutions, PathExplore, is an artificial intelligence-powered panel of histopathology features that offers an unprecedented spatial and cellular resolution of the tumor microenvironment (TME) from H&E images. It can be used in healthcare research to improve the quantification of established disease signatures and to identify novel histological biomarkers and drivers of therapeutic efficacy. Another solution called AISight, PathAI's web-based digital pathology slide viewing platform, enables the management and analysis of whole slides or medical images with features such as magnification presets, information annotations with commenting, and side-by-side slide viewing.


Enlitic Curie is an extensible data management framework that features a host of deep learning-powered applications. These AI systems enable data standardization, retrospective and real-time analysis, research, risk mitigation, and workflow simplification. The Enlitic Curie framework forms the basis for a real-world medical imaging database that integrates with and enhances other information sources such as electronic health records or patient management systems. The framework provides connectivity to modalities, PACS, EMR, and other information systems. One of Enlitic's solutions, Curie ENDEX, is medical imaging software that uses AI to ensure data is normalized to a standardized nomenclature. It means that the relevant series are routed to the appropriate AI algorithms, and results are labeled with clinically relevant descriptions or imaging professionals. Healthcare data management solutions Curie ENCOG anonymizes and protects medical imaging data. With ENCOG, data is cleaned of all PHI contained in the metadata, pixel data, and tags. But, all the high-value clinical information remains intact. 


Regard, founded in 2017, enhances healthcare by offering an AI solution that enables doctors to make precise patient diagnoses. Using machine learning algorithms, Regard was purposefully designed for physicians to streamline workflow, enabling efficient use of EHRs. The company's AI co-pilot embeds into the EHR and works as a virtual medical resident to curate all patient data, suggest new diagnoses, and automatically generate clinical notes. Regard's 'Medical Co-pilot' recognizes about 50 of the most prevalent medical illnesses, including heart failure, kidney disease, pneumonia, COVID-19, anxiety and depression, respiratory failure, and sepsis. Moreover, regard is proven to drive DRG upgrades by capturing previously undocumented CCs, MCCs, and HCCs. The platform also streamlines clinical, CDI, and revenue cycle management efforts to dramatically improve hospital finances, patient safety, and physician happiness. 


Twill is an intelligent healing company that combines digital therapeutics, well-being products, community-based care, clinician-trained AI, and live coaching. It provides three digital products, namely Twill Care, Twill Therapeutics, and Happify. Twill Care app provides personalized, condition-specific content like articles, videos, and infographics to educate and guide patients based on their entire medical history as they work with healthcare providers to manage chronic conditions or life stages. Twill Therapeutics app offers Duet, a live behavioral coaching that fits into patients' rhythm with proactive, synchronous, and asynchronous interactions, all while measuring emotional well-being and tracking progress. Twill's Happify app offers mental health programs that guide members through goal-based journeys based on clinical data. Some of their most popular programs include Fueling a Successful Career, Conquering Negative Thoughts, and Building Mindfulness Through Meditation.


Murf is a leading text to speech platform, which offers AI voices in 20+ languages that can be used for speech functions in health applications, healthcare devices voices, and nurse call systems. Murf TTS tool can also be used to generate voiceovers for training materials, learning and development presentations, videos on corporate compliance, medical records, and more. For instance, Murf can be leveraged to convert complex medical documentation into an interactive video or presentation, enabling medical staff to understand the info more seamlessly. 

Murf's AI voices can deliver detailed audio instructions on operating life-saving AED medical devices and allow hospital patients to request a nurse or doctor through systems. Medical professionals can also incorporate an audio feedback component to electronic prescriptions, clinical notes, or patient notes using Murf. Using AI voices, healthcare organizations can also personalize and schedule outbound calls in IVR with reminders about upcoming appointments, cancellation policies, and more. Doing so increases accuracy and proficiency while reducing errors. TTS tools also improve the ability to communicate, retain information, and comprehension of people with disabilities through its voice over features, making them independent in their learning process. 

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Future of Artificial Intelligence in Healthcare 

Given the large-scale expansion of AI capabilities, it is only logical to question what the future holds for AI in healthcare sector. Machine learning has many potential usecases in the healthcare industry, from diagnostics and treatment planning to patient care and safety. These applications are bound to advance as technology does.

By enhancing patient outcomes, lowering costs, and boosting efficiency based on data stored, AI has the potential to completely transform the healthcare sector. AI-powered systems can enhance patient monitoring and allow for real-time analysis of massive volumes of health data, resulting in better results and more informed decisions. The use of AI and data science will cut the waiting time and enhance communication between patients and healthcare professionals, improving overall patient experiences and decreasing health inequities. As AI technology develops, we may anticipate more sophisticated and precise healthcare solutions that will help patients, providers, and society at large. For instance, monitoring vital signs in real-time and spotting potentially harmful situations even before they arise on a larger scale. Machine learning will also make the training of medical students easy and more interesting through naturalistic simulations that give a real-time experience.

With the AI revolution on the brink, it is only right to anticipate much bigger medical care advancements that will enhance countless people's lives worldwide, changing the face of healthcare forever. 


What are the five uses of AI in the medical field?

AI in healthcare can be used in drug creation and discovery in a research lab, disease diagnosis and treatment, precision medicine, surgery assistance, and administrative assistance. 

What is new AI technology in healthcare?

Using surgical robots for minimally invasive procedures is a reasonably new advancement that is rapidly gaining momentum.

What problems can AI solve in healthcare?

Using AI technologies, medical professionals can avoid errors in disease diagnosis and treatment. Machine learning can help with faster drug discovery and creation, which can take ample time otherwise.

How does AI help in health care? 

Healthcare industry benefits from AI adoption in several ways, including in more accurate diagnoses of malignant diseases even before their occurrence. It streamlines clinical workflows through personalized treatments and surgeries. 

How does AI improve the quality of healthcare?

Using AI in their clinical practice, healthcare professionals can automate previously time-consuming jobs with minimum errors to save time and costs, thus improving the overall quality of healthcare. 

Is AI the future of healthcare?

Yes, considering the rapid growth and utilization of AI technology in the medical section for life-saving procedures, AI is the future of healthcare. We will see several AI companies undertake substantial integration projects.

What is the role of AI in healthcare sector in India?

Besides assisting in treatment applications diagnosis, decreasing health inequities, and treatment of malignant diseases such as cancer and heart failure, AI is streamlining various research and administrative tasks for medical providers, such as drug discovery, healthcare data management, converting complex documents into speech, and more in India.