AI for HealthTech: AI’s remarkable impact on patient outcomes & medical advancements

AI has been upping the game in healthcare, providing much more hope for patients of diseases like cancer, while making life easier for doctors and healthcare professionals.

Recently, Former Google CEO Eric Schmidt talked about the potential for AI to transform healthcare in the MIT Technology Review.

With the advent of AI, science is about to become much more exciting—and in some ways unrecognizable. The reverberations of this shift will be felt far outside the lab; they will affect us all

Eric Schmidt, Former Google CEO

“With the advent of AI, science is about to become much more exciting—and in some ways unrecognizable. The reverberations of this shift will be felt far outside the lab; they will affect us all,” he says.

He included examples of scientists at McMaster and MIT identifying an antibiotic to combat a dangerous antibiotic-resistant bacteria, a Google DeepMind model controlling plasma in nuclear fusion reactions, leading to a clean-energy revolution, and the FDA clearing 500+ devices that use AI, with many aimed at improving radiology.

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Advancements in AI are beginning to deliver breakthroughs in breast cancer screening by detecting the signs that doctors miss. In a study, the results of which were published in Radiology, in thousands of mammograms, AI algorithms outperformed the standard clinical risk model for predicting the five-year risk for breast cancer.

In June, Mount Sinai researchers developed an innovative AI model for electrocardiogram (ECG) analysis that lets ECGs be interpreted as language. This can boost the accuracy and effectiveness of ECG-related diagnoses, especially for cardiac conditions where limited data is available on which to train.

Scientists at McMaster University and the MIT used AI to discover a new antibiotic that could be used to fight a deadly, drug-resistant pathogen that targets susceptible hospital patients.

ChatGPT is part of the process. In June, researchers at MIT and Tufts University developed a new AI model called ConPLex that speeds up drug discovery by predicting drug-protein interactions without the need to calculate the molecules’ structures.

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Many startup companies are saying that programs like ChatGPT could complete doctors’ paperwork for them. Although, some experts have concerns about inherent bias and the tendency to make up facts leading to errors.

In February, Indian company Thyrocare, a preventive healthcare diagnosis platform, announced the adoption of AI-powered technology, SigTuple’s AI100, to automate the manual microscopy process across its network. 

According to the doctors involved, AI can significantly reduce the turnaround time, standardise reporting quality and increase efficiency multi-fold. Rahul Guha, Managing Director of Thyrocare Technologies, said, “Digitalising microscopy has the potential to transform the face of diagnostics throughout India, and AI-integration in diagnostics is a game-changer. It has brought remarkable precision to our diagnostic capabilities.”

AI-integration in diagnostics is a game-changer. It has brought remarkable precision to our diagnostic capabilities

Rahul Guha, Managing Director of Thyrocare Technologies

He adds that digital microscopy with AI will be an enabler in a big way to do peer review on abnormal samples reporting and diagnosing several critical disorders like malarial infections, cancers, etc. AI brings down the scan time significantly which gives leverage to labs to report quickly. The scan data is available for secondary opinion, sharing with clinicians in a digital format.

Along with detailed haematology image analysis, AI models comprehensively investigate medical metadata for precision medicine

Dr. Preet, Head Clinical Operations & Quality, Thyrocare Technologies

Dr. Preet, Head Clinical Operations & Quality, Thyrocare Technologies added, “One important advantage of pathological AI models is reduced errors in diagnosis. These models assist in automatic detection, quantification of haematology parameters, and accurate disease diagnosis. Along with detailed haematology image analysis, AI models comprehensively investigate medical metadata for precision medicine.” 

World over, it is strongly believed that AI-assisted digital microscopy is the way forward for pathology. Digital microscopy is the process in which a physical sample is digitally imaged through a microscopic lens. This makes it possible for pathologists to review them with ease in digital format. AI helps increase efficiency by automating most of the review.