Tag: Diagnosis

Venture capitalist Vinod Khosla predicted AI's impact on healthcare, and today we see numerous startups utilizing AI & machine learning to revolutionize the industry. Khosla's history of taking risks in areas with great potential, offers insight into the future of healthcare investments.

Ezra's full-body MRI scanner detects potential signs of cancer and monitors hundreds of other conditions for early detection. Accessible and affordable to all, Ezra uses AI and aims to improve survival rates.

Discover a new machine learning solution for autism detection that uses a non-invasive approach and advanced Federated Learning. With 99% accuracy, this model is designed to detect ASD at different age stages with maximum accuracy, controlled expenses, and minimum time.

A new study published in Scientific Reports found that a machine learning algorithm predicts a person's level of daytime sleepiness using electroencephalography (EEG) data. The algorithm was 88% accurate in predicting severe sleepiness, potentially leading to the development of non-invasive methods for diagnosing and monitoring sleep disorders like sleep apnea and narcolepsy. Dr. Lara V. Marcuse, the study's lead author, notes that further research is needed to verify these results.

A new study reveals that a machine learning model that combines cardiac troponin concentrations with clinical features can improve the diagnosis of myocardial infarction. This can lead to less time in emergency departments, fewer hospital admissions, and better early treatment.