PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...

Magnetic resonance imaging (MRI) radiomics as predictor of clinical outcomes to neoadjuvant immunotherapy in patients with muscle invasive bladder cancer undergoing radical cystectomy. This is an ASCO ...

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success ...

TrialTranslator uncovers the survival gap for high-risk patients and offers a path to better cancer research. Study: Evaluating generalizability of oncology trial results to real-world patients using ...

When it comes to training artificial intelligence, OpenAI and Babylon Biosciences have shown that experienced hands can help steer the programs toward greater accuracy through a collaboration aimed at ...

The Cleveland Clinic has partnered with newcomer Dyania Health to identify a broader array of patients for clinical trials using artificial intelligence. The Cleveland Clinic runs a massive research ...

Please provide your email address to receive an email when new articles are posted on . In this episode, host Shikha Jain, MD, speaks with Opyl co-founder Damon Rasheed about using machine learning to ...

Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...

The topic of AI and its implications for orthopedic surgeons became of high personal importance when Bill Gates predicted that AI would replace physicians and others within the next decade. As an ...