AI Tool Helps Predict Relapse of Pediatric Brain Cancer
Artificial intelligence (AI) shows tremendous promise for analyzing vast medical imaging datasets and identifying patterns that may be missed by human observers. AI-assisted interpretation of brain scans may help improve care for children with brain tumors called gliomas, which are typically treatable but vary in risk of recurrence.
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AI-Powered Analysis of Stent Healing
Each year, more than three million people worldwide are treated with stents to open blocked blood vessels caused by heart disease. However, monitoring the healing process after implantation remains a challenge. If the tissue growing over the stent develops irregularly - either becoming too thick or forming deposits - it can lead to complications, such as re-narrowing or occlusion of the blood vessel.
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Right Patient, Right Dose, Right Time
While artificial intelligence (AI) has shown promising potential, much of its use has remained theoretical or retrospective. Turning its potential into real-world healthcare outcomes, researchers at the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine) have successfully utilised an AI platform to make precise recommendations for dose adjustments in 10 patients at the National University Cancer Institute, Singapore (NCIS) in Singapore.
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Detecting Lung Cancer 4 Months Earlier at the GP Using AI
GPs may soon be able to identify patients with an increased risk of lung cancer up to 4 months earlier than is currently the case. The GP should be able to simply identify patients during a consultation with an algorithm created by researchers at Amsterdam UMC based on the data of more than half a million patients.
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An AI Tool Grounded in Evidence-Based Medicine Outperformed Other AI Tools
A powerful clinical artificial intelligence tool developed by University at Buffalo biomedical informatics researchers has demonstrated remarkable accuracy on all three parts of the United States Medical Licensing Exam (Step exams), according to a paper published in JAMA Network Open.
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Generative AI's Diagnostic Capabilities Comparable to Non-Dpecialist Doctors
The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were different for each study, a comprehensive analysis was needed to determine the extent AI could be used in actual medical settings and what advantages it featured in comparison to doctors.
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Diagnoses and Treatment Recommendations Given by AI were More Accurate than those of Physicians
A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations made by artificial intelligence (AI) and physicians at Cedars-Sinai Connect, a virtual urgent care clinic in Los Angeles, operated in collaboration with Israeli startup K Health. The paper was published in Annals of Internal Medicine and presented at the annual conference of the American College of Physicians (ACP).
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