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Posted: 14 Mar 2019

Top 11 AI Applications in Healthcare | Mindfields

By Mohit Sharma

We are increasingly seeing tangible impact of AI trends in healthcare across various industries, including healthcare. AI is helping key stakeholders like hospitals, diagnostic labs and pharmaceutical companies in various ways. 

Top 11 AI use cases in Healthcare:

Healthcare “Data Mining” with AI can predict diseases

In the era of ubiquitous technology, data becomes an important fuel to drive innovation. Data mining is being deployed to find insights and patterns from large databases. The healthcare industry captures large volumes of patient records. With appropriate analysis of this data, using machine learning tools, the healthcare sector can address a plethora of diseases prior to their occurrence.

Currently, the healthcare industry employs data mining to develop early detection systems by using clinical and diagnosis data. Tech giants, such as Google and IBM are using AI to unearth patient data which are structured and unstructured. The data is extracted by mining the medical records or by deciphering physician-patient interaction (voice and non-voice based interactions).

AI in “Medical Imaging and Diagnostics” provides precise information

Over the past couple of years, as a top example for AI use cases in healthcare it is witnessed that AI has expanded substantially in the fields of medical imaging and diagnostics, thereby enabling medical researchers and doctors to deliver flawless clinical practice. Paving the way for quantification and standardization, deep learning is aiding in prevention of errors in diagnostics and improving the test outcome.

Further, AI is improving the assessment in medical imaging to detect cases such as malignancy and Diabetic Retinopathy (DR). It is also assisting with quantifying blood flow and providing visualization. According to European Radiology Experimental’s recent poll, over 50% of global healthcare leaders expect the role of AI in monitoring and diagnosis to grow significantly. Recently, Arterys, a Deep Learning medical imaging technology company, partnered with General Electric (GE) Healthcare. This partnership combines Arterys’ quantification and medical imaging technology with GE Healthcare’s Magnetic Resonance (MR) cardiac solutions. By collaborating these technologies, it is now possible to conduct cardiac assessments in a fraction of the time as compared to the conventional cardiac MR scans.

AI in “Lifestyle Management and Monitoring” is changing the way we live

A very important aspect of AI use cases in healthcare sector is the increase in digitization that enables individuals to manage their own health and comfort. Data generated from digitization fuels the AI technology of tomorrow. Today, parents can monitor their infants to check their health, sleeping patterns and development. Recently, Fedo, a start-up, found a solution to encounter individual’s risks for lifestyle diseases. They have developed a risk stratification algorithm, using AI, to predict individuals’ readiness for 7 noncommunicable diseases such as Diabetes II and Cardiovascular disease – Myocardial Infarction.

AI in “Nutrition” is enhancing the journey to a healthy and fit lifestyle

Currently, an extensive number of nutrition related apps are available in stores, with different functions and accuracies. With the integration of AI, nutrition apps can become a very good example to AI use cases in healthcare sector, which can give customized recommendations and suggestions based on a person's preferences and habits. VITL, a start-up based in London, is applying AI to diagnose patients’ nutritional needs and deficiencies. Along with the diagnosis, it further provides users with a bespoke nutrition plan and daily vitamin pack. To map out the logic and thought process of human nutrition experts, the start-up uses an AI engine called LANA (Live and Adaptive Nutritional Advisor) which employs a broad range of lifestyle and diet data points.

AI in “Emergency Room and Surgery” is saving lives

The first surgical robot, named as da Vinci Surgery System, which was approved by the FDA for general laparoscopic surgery, was developed about 15 years ago. Since then, many other surgical robots were introduced, including the current generation of robots which are integrating AI in surgery. The next generation of surgical robots are being powered by machine learning and AI. In the near future, we will witness AI platforms such as DeepMind, IBM Watson and other advanced AI tools enabling physicians and hospitals to deliver promising surgical interventions. IBM Watson has advanced medical cognitive and NLP capabilities to respond to surgeon’s queries. Further, similar AI platforms aid in monitoring blood in real time, detect physiological response to pain, and can provide navigation support in arthroscopy and open surgery.

AI in “Hospital Information System (HIS)” can enrich the delivery of healthcare services

Currently most of the hospitals and clinics have HIS software to handle the process of appointment, treatment follow-up, and other administrative processes, by integrating with EHRs of patients. There is great potential for these systems to be used for offering superior health services. For instance, Google’s DeepMind Health team is working with NHS hospitals to monitor a patient’s conditions via a mobile application. The app allows the hospitals to promptly identify any deterioration in the patient’s conditions and thus provide treatment as quickly and accurately as possible. Furthermore, AI in healthcare provides support to clinicians for predictive analytics in real-time and solves operational challenges across the hospital functions. It also saves staff time, reduces steps, and removes paper-based processes through automated data collection, analysis, reporting and communication.

AI in “Research” is providing fascinating insights

AI enables healthcare providers to create a digital profile of humans. This can help in understanding immunosequence, thereby generating a new class of immune diagnostics in oncology. Additionally, it is being used to accomplish reproducible research in bioinformatics, genomics and life science. Adaptive Biotechnologies, a start-up addressing genomic based therapy, partnered with Microsoft to find out insights of immnosequence.

AI in “Mental Health” is building a strong support system for patients

While talking about AI use cases in  healthcare, let's not miss out on AI in "mental heath". We live in a world where 1 in 4 people suffer from mental disorders, making it one of the leading causes of disability and ill-health. Healthcare, being relatively slow in adoption of new technologies, has seen some of the greatest advances in AI recently including early identification of mental health symptoms. Certain factors such as a person’s tone, word choice, and the duration of a phrase are considered when studying an individual..

Wysa, an AI-based emotionally intelligent penguin, developed by Touchkin, can listen, chat and help users build mental resilience. Within 3 months, Wysa had witnessed a million chats with 50,000 users and assisted them to overcome mental health troubles. Some of these users had been suicidal, others lived with Post traumatic stress disorder (PTSD), social anxiety, depression, or bipolar disorders. Thus, for the millions of people who feel lonely and need the support of friends and psychiatric therapists, AI can build resilience, offer support, and save lives.

AI in “Pharma” is enabling the discovery of a new class of diagnostics and treatment

AI is revolutionizing the way pharmaceutical companies develop medicines. AI searches biological systems to understand how a drug can affect a patient’s tissues/cells. For instance, applications like precision medicine and predictive medicine are used to predict a patient’s treatment rather than investigating a bigger set of patients. BERG, a pharmaceutical start-up, has created an AI platform that uses biological data as cells transform from healthy to malignant ones. The software utilizes information from the 2003 Human Genome Project in addition to over 14 trillion data points in a single cell tissue. This research allowed BERG to develop a new cancer drug that could potentially reverse this process.

AI technology in “Virtual Assistant” to communicate with patients in an efficient way

AI use cases in healthcare can also be discussed primarily with the introduction of Virtual Assistants/AI assistants being created to help and enhance human-like interactions, thereby saving time and resources. Nuance, a company which has developed a Medical Virtual Assistant, streamlines clinical workflows for the 500,000 clinicians who rely on Dragon Medical every day for their clinical documentation. It enables individuals who are using specialized medical terminologies to communicate naturally with high accuracy.

AI in “Wearables” is making us proactive to take healthy decisions

Miniaturization is the upcoming trend in AI applications and thus, wearables such as smart-watches, clothes, and shoes will be trending in near future. Researchers and manufacturers alike are looking to benefit from this trend by making it available for everyday use and clinical grade applications. In the absence of an AI engine, the data from a product would yield zero value to the user. Hence, AI engines are being integrated within the product’s health solutions to capture health insights of an individual. Thus, on detection of an abnormality through clinical grade wearable technology, users can approach the physician or can also opt for an AI doctor.

At Mindfields, we have been driving innovation and excellence by leveraging disrupting technologies to optimize business processes that enable our clients to 'Grow for tomorrow'. To learn more about applications of Artificial Intelligence in Healthcare and the technology landscape, download Mindfields’ AI in Healthcare report.

Mohit Sharma

Mohit Sharma

Founder and Exec Chairman
Thought Leader | Trusted Advisor | Innovator