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Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.

OBJECTIVES: This study aims to (1) review machine learning (ML)-based models for early infection dia...

A machine learning framework to adjust for learning effects in medical device safety evaluation.

OBJECTIVES: Traditional methods for medical device post-market surveillance often fail to accurately...

Leveraging Generative AI for Drug Safety and Pharmacovigilance.

Predictions are made by artificial intelligence, especially through machine learning, which uses alg...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

Prediction of Post Traumatic Epilepsy Using MR-Based Imaging Markers.

Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic ...

Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

MOTIVATION: Post-translational modification (PTM) crosstalk events play critical roles in biological...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first ...

AI Prediction for Post-Lower Blepharoplasty Age Reduction.

BACKGROUND: Aesthetic standards vary and are subjective; artificial intelligence (AI), which is curr...

Toward a responsible future: recommendations for AI-enabled clinical decision support.

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to ben...

Prediction of Post-Treatment Visual Acuity in Age-Related Macular Degeneration Patients With an Interpretable Machine Learning Method.

PURPOSE: We evaluated the features predicting visual acuity (VA) after one year in neovascular age-r...

Comparative Analysis of Macular and Optic Disc Perfusion Pre and Post Silicone Oil Removal: A Machine Learning Approach.

In the realm of ophthalmic surgeries, silicone oil is often utilized as a tamponade agent for repair...

Causal Deep Learning for the Detection of Adverse Drug Reactions: Drug-Induced Acute Kidney Injury as a Case Study.

Causal Deep/Machine Learning (CDL/CML) is an emerging Artificial Intelligence (AI) paradigm. The com...

Enhancing Pulmonary Embolism Detection in COVID-19 Patients Through Advanced Deep Learning Techniques.

The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medic...

The Effects of Robotic Exoskeleton Gait Training on Improving Walking Adaptability in Persons with MS.

The goal of the present pilot investigation is to examine the effects of 8 weeks of supervised, over...

Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework.

Aphasia, a language disorder primarily caused by a stroke, is traditionally diagnosed using behavior...

Transformer-Based Wavelet-Scalogram Deep Learning for Improved Seizure Pattern Recognition in Post-Hypoxic-Ischemic Fetal Sheep EEG.

Hypoxic-ischemic (HI) events in newborns can trigger seizures, which are highly associated with late...

Prediction of Postinduction Hypotension by Machine Learning.

Post-induction hypotension (PIH) occurs shortly after anesthesia induction and is related to several...

Temporal Convolutional Network for Gait Event Detection.

In this study, we propose a novel deep learning-based framework for automatic gait event detection (...

Artificial Intelligence on The Couch. Staying Human Post-AI.

This paper examines the human relationship to technology, and AI in particular, including the propos...

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