If verified in additional trials, the advance will facilitate care planning much earlier than the current average age of diagnosis, 4 years old.
AI can be taught to flag possible skin cancers on photos taken with smartphone cameras—and the images can be ordinary “people shots” rather than closeups of suspicious lesions.
Only two of 34 representative studies evaluating the use of AI for real-world shared clinical decisionmaking from 2014 to 2020 included external validation of the models up for consideration.
Healthcare AI is advancing too quickly for its users to fully comprehend the implications of its design, development and applications, according to bioethics specialists who scanned the literature.
The tool makes the call based on factors readily available to busy clinicians, respecting their workflows while helping patients and families decide whether moving to access a stepped-up care setting would fit well with their aims and values.
Two bioinformatics experts have used AI to accurately estimate regional COVID infection rates, aka seroprevalence, in all 50 states and 50 hard-hit countries.
The plan is to draw health data from every available source to continuously nudge individuals toward not only appropriate medical care but also healthier lifestyles.
Computer engineers have produced a deep learning framework for very quickly fine-tuning vaccines to fight emerging variant strains of COVID-19.
The FDA has OK’d AI software that can predict worsening condition in ICU patients up to eight hours before the falloff produces symptoms.
AI has proven capable of automatically detecting looming heart trouble on CT scans taken for lung issues like lung cancer, pulmonary embolism and pneumonia.
The idea is to head off serious gathering threats without getting thrown off the scent by strains unlikely to proliferate.
AI melanoma detectors that equaled or bettered dermatologists in clinical trials have stumbled on the way to the real world of patient care.