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Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal.

Acta orthopaedica
Background and purpose - Artificial intelligence (AI), deep learning (DL), and machine learning (ML) have become common research fields in orthopedics and medicine in general. Engineers perform much of the work. While they gear the results towards he...

Effectiveness of robotic-assisted therapy for upper extremity function in children and adolescents with cerebral palsy: a systematic review protocol.

BMJ open
INTRODUCTION: The application of advanced technologies in paediatric rehabilitation to improve performance and enhance everyday functioning shows considerable promise. The aims of this systematic review are to investigate the effectiveness of robotic...

Procurement, commissioning and QA of AI based solutions: An MPE's perspective on introducing AI in clinical practice.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: In this study, we propose a framework to help the MPE take up a unique and important role at the introduction of AI solutions in clinical practice, and more in particular at procurement, acceptance, commissioning and QA.

Pig Weight and Body Size Estimation Using a Multiple Output Regression Convolutional Neural Network: A Fast and Fully Automatic Method.

Sensors (Basel, Switzerland)
Pig weight and body size are important indicators for producers. Due to the increasing scale of pig farms, it is increasingly difficult for farmers to quickly and automatically obtain pig weight and body size. Due to this problem, we focused on a mul...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Nature protocols
Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electron...

5335 days of Implementation Science: using natural language processing to examine publication trends and topics.

Implementation science : IS
INTRODUCTION: Moving evidence-based practices into the hands of practitioners requires the synthesis and translation of research literature. However, the growing pace of scientific publications across disciplines makes it increasingly difficult to st...

Machine Learning-Based Prediction of Growth in Confirmed COVID-19 Infection Cases in 114 Countries Using Metrics of Nonpharmaceutical Interventions and Cultural Dimensions: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: National governments worldwide have implemented nonpharmaceutical interventions to control the COVID-19 pandemic and mitigate its effects.

Charting a path forward for clinical research in artificial intelligence and gastroenterology.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Gastroenterology has been an early leader in bridging the gap between artificial intelligence (AI) model development and clinical trial validation, and in recent years we have seen the publication of several randomized clinical trials examining the r...

Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.