Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
As the International Olympic Committee (IOC) embraces AI-assisted judging, this technology promises greater consistency and ...
Recently, the UK’s tax and accounting professional bodies published updated guidance on the ethical use of AI in tax work, aligned to the Professional ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Performing moderate-to-vigorous aerobic exercise for 12 months can reduce a brain-age biomarker, brain-predicted age ...
Abstract: This paper attempts to construct a prediction model for identifying the likelihood of patient readmission based on electronic health records (EHR) of the UCI Diabetes dataset. It employs the ...
A new study published in the Journal of Orthopaedic Research indicates that an artificial intelligence–based model trained on basic blood and lab test data as well as basic demographic data can ...
Abstract: In this paper the authors have implemented stiction detection using machine learning algorithm. Valve stiction is a common nonlinearity in pneumatic control valves that can significantly ...
An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
Objective: Prophylactic dissection of lymph nodes posterior to the recurrent laryngeal nerve (LN-prRLN) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) remains controversial due to ...
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