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Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

American journal of respiratory and critical care medicine
Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. Apply multiple instance learning (MIL) to develop an explainable ...

Don't Fear the Artificial Intelligence: A Systematic Review of Machine Learning for Prostate Cancer Detection in Pathology.

Archives of pathology & laboratory medicine
CONTEXT: Automated prostate cancer detection using machine learning technology has led to speculation that pathologists will soon be replaced by algorithms. This review covers the development of machine learning algorithms and their reported effectiv...

An interpretable machine learning model to predict off-pump coronary artery bypass grafting-associated acute kidney injury.

Advances in clinical and experimental medicine : official organ Wroclaw Medical University
BACKGROUND: Off-pump coronary artery bypass grafting-associated acute kidney injury (OPCAB-AKI) is related to 30-day perioperative mortality. Existing mathematical models cannot be applied to help clinicians make early diagnosis and intervention deci...

Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model.

Croatian medical journal
AIM: To compare the effectiveness of artificial neural network (ANN) and traditional statistical analysis on identical data sets within the splenectomy-middle carotid artery occlusion (MCAO) mouse model.

Prognostic value of a novel artificial intelligence-based coronary computed tomography angiography-derived ischaemia algorithm for patients with suspected coronary artery disease.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims...

Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images.

Dento maxillo facial radiology
OBJECTIVES: The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in cone beam computed tomography (CBCT) volumes and to evaluate the performance of this model.

Neural Network-Based Prediction of Perceived Sleep Quality Through Wearable Device Data.

Studies in health technology and informatics
BACKGROUND: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, ph...

Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study.

Studies in health technology and informatics
BACKGROUND: Malnutrition in hospitalised patients can lead to serious complications, worse patient outcomes and longer hospital stays. State-of-the-art screening methods rely on scores, which need additional manual assessments causing higher workload...

Acceptance of Telepresence Robotics, Telecare and Teletherapy Among Stroke Patients, Relatives and Therapy Staff.

Studies in health technology and informatics
BACKGROUND: Stroke as a cause of disability in adulthood causes an increasing demand for therapy and care services, including telecare and teletherapy.