6 AI applications already in use in the healthcare industry

Sam Altman, co-founder and CEO of artificial intelligence firm OpenAI, released an essay on Sept. 23 proclaiming the arrival of the “Intelligence Age.”

In it, he claimed that humanity would see exponential advancement through artificial intelligence including “fixing the climate, establishing a space colony, and the discovery of all of physics – will eventually become commonplace.”

Many criticized his statements as the usual pie-in-the-sky ideas that have been coming out of Silicon Valley for years.

But there are already several areas of study and scientific development where AI is playing an important role.

From accelerating drug discovery to enhancing medical imaging, AI is undoubtedly contributing to scientific inquiry and healthcare delivery.  

Here are just eight projects using AI to push science to its cutting edge.

Ultrasound imaging — GE Verisound AI

Using its proprietary AI software, GE Verisound AI is making it easier for non-experts to capture high-quality ultrasound images of the heart, allowing for earlier disease detection.

One of the company’s flagship offerings, Caption AI, provides real-time visual guidance to users, prompting them on probe movements and providing a quality meter to ensure that only high resolution images are captured.  

Once an image has been acquired, the device’s AutoEF feature uses AI-driven algorithms (trained using voluminous medical data) to calculate critical measures of a patient’s heart health, such as the left ventricular ejection fraction, which is a measure of how much blood is pumped out of the heart’s main pumping chamber with each beat.

Drug discovery — Atomwise

San Francisco-based Atomwise is using AI for the drug discovery process. Their AtomNet platform uses convolutional neural networks, a technology similar to that enabling self-driving cars, to predict the efficacy of potential drug candidates before they enter costly clinical trials.

By analyzing experimental affinity measurements and protein structures, AtomNet can predict how small molecules will bind to proteins, significantly accelerating the identification of effective and safe drug candidates. 

This approach has the potential to dramatically reduce the time and cost associated with bringing new medicines to market.

As part of an April 2024 study, Atomwise successfully identified novel drug candidates for 235 out of 318 targets evaluated across collaborations with over 250 academic labs in 30 countries. 

Radiology — Behold.ai and Enlitic

Behold.ai has been developing AI-assisted radiology with its “red dot” algorithm. Based on deep learning models trained on over 30,000 images, the company’s proprietary software can classify chest X-rays and localize findings as heatmaps.

The algorithm claims a 90% accuracy ratio in detecting abnormalities within seconds, significantly reducing the workload on radiologists and decreasing waiting times for diagnoses. 

In a May 2023 case study with the NHS, Behold.ai’s solution demonstrated a 29% reduction in radiologists’ workload and a 71% reduction in diagnosis waiting times.

Similarly, Enlitic is another firm using deep learning to interpret medical images — estimated to be 10,000 times faster than the average radiologist.

In fact, as part of an October 2019 study, the company’s AI-powered solutions demonstrated the ability to detect malignant lung nodules up to 18 months before a biopsy.

Speech assistance and recognition — Voiceitt

Voiceitt has developed a communication stack for individuals with speech impairments by using AI-driven speech recognition technology. By automating the process of understanding atypical speech, Voiceitt offers solutions like voice-controlled smart devices and customized communication tools. 

Moreover, its integration with platforms like Webex, Microsoft Teams and Zoom improves accessibility in virtual meetings through real-time captioning and transcription. 

The company aims to empower individuals with speech disabilities to enhance their independence and participate more fully in both personal and professional environments.

Clinical decision making— Merative

Formerly known as IBM Watson Health, Merative is a healthcare technology company that uses AI for clinical decision-making.

By integrating AI with a patient’s healthcare — and using predictive analytics and natural language processing (NLP) — the company helps clinicians make more informed choices.

Marative’s solutions can personalize medicine prescriptions, streamline healthcare operations, and optimize resource management.

Healthcare delivery automation — WELL Health Technologies

WELL Health Technologies, Canada’s largest outpatient clinic operator, uses AI to streamline healthcare delivery by automating administrative tasks like appointment scheduling, data analysis and patient follow-ups.

Their AI solutions also assist with diagnostics, triage, and remote monitoring, aiding early disease detection and ongoing health tracking. In July 2024, WELL launched an AI-powered co-pilot for cardiologists, improving cardiovascular disease management.