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The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological Patients.

International journal of environmental research and public health
Advance assessment of the potential functional improvement of patients undergoing a rehabilitation program is crucial in developing precision medicine tools and patient-oriented rehabilitation programs, as well as in better allocating resources in ho...

Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning.

Artificial intelligence in medicine
Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources o...

A Conceptual Framework to Predict Disease Progressions in Patients with Chronic Kidney Disease, Using Machine Learning and Process Mining.

Studies in health technology and informatics
Process Mining is a technique looking into the analysis and mining of existing process flow. On the other hand, Machine Learning is a data science field and a sub-branch of Artificial Intelligence with the main purpose of replicating human behavior t...

Representation of time-varying and time-invariant EMR data and its application in modeling outcome prediction for heart failure patients.

Journal of biomedical informatics
OBJECTIVE: To represent a patient record with both time-invariant and time-varying features as a single vector using an end-to-end deep learning model, and further to predict the kidney failure (KF) status and mortality of heart failure (HF) patients...

Deep Learning Algorithm for Tumor Segmentation and Discrimination of Clinically Significant Cancer in Patients with Prostate Cancer.

Current oncology (Toronto, Ont.)
BACKGROUND: We investigated the feasibility of a deep learning algorithm (DLA) based on apparent diffusion coefficient (ADC) maps for the segmentation and discrimination of clinically significant cancer (CSC, Gleason score ≥ 7) from non-CSC in patien...

Supporting primary care through symptom checking artificial intelligence: a study of patient and physician attitudes in Italian general practice.

BMC primary care
BACKGROUND: Rapid advancements in artificial intelligence (AI) have led to the adoption of AI-driven symptom checkers in primary care. This study aimed to evaluate both patients' and physicians' attitudes towards these tools in Italian general practi...