AI Medical Compendium Topic:
Delivery of Health Care

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Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda.

BMC pregnancy and childbirth
Machine Learning (ML) has been widely used in predicting the mode of childbirth and assessing the potential maternal risks during pregnancy. The primary aim of this review study is to explore current research and development perspectives that utilize...

A systematic review on the usability of robotic and virtual reality devices in neuromotor rehabilitation: patients' and healthcare professionals' perspective.

BMC health services research
BACKGROUND: The application of virtual reality (VR) and robotic devices in neuromotor rehabilitation has provided promising evidence in terms of efficacy, so far. Usability evaluations of these technologies have been conducted extensively, but no ove...

Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques.

Computational intelligence and neuroscience
A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common for them to be battery-powered and responsive to a nearby controller, referred to as the base station...

Machine Learning for Healthcare Wearable Devices: The Big Picture.

Journal of healthcare engineering
Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and vital signs using wearable dev...

Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications.

IEEE journal of biomedical and health informatics
AI healthcare applications rely on sensitive electronic healthcare records (EHRs) that are scarcely labelled and are often distributed across a network of the symbiont institutions. It is challenging to train the effective machine learning models on ...

Online Disease Identification and Diagnosis and Treatment Based on Machine Learning Technology.

Journal of healthcare engineering
The article uses machine learning algorithms to extract disease symptom keyword vectors. At the same time, we used deep learning technology to design a disease symptom classification model. We apply this model to an online disease consultation recomm...

Somatic Genome Editing with the Use of AI: Big Promises but Doubled Legal Issues.

European journal of health law
Both Artificial Intelligence ('AI') and genome editing are technologies that on their own promise to revolutionise healthcare. But their common application can facilitate progress in the field even more. Multiplied benefits go along with increased ri...

Engaging children and young people on the potential role of artificial intelligence in medicine.

Pediatric research
INTRODUCTION: There is increasing interest in Artificial Intelligence (AI) and its application to medicine. Perceptions of AI are less well-known, notably amongst children and young people (CYP). This workshop investigates attitudes towards AI and it...

Deep Data Analysis-Based Agricultural Products Management for Smart Public Healthcare.

Frontiers in public health
Agricultural is an indispensably public healthcare industry for human beings at any time and smart management of it is of great significance. Since substantial technical advance relies on long-term efforts and continuous progress, reasonably scheduli...

Effectiveness of Artificial Intelligence for Personalized Medicine in Neoplasms: A Systematic Review.

BioMed research international
PURPOSE: Artificial intelligence (AI) techniques are used in precision medicine to explore novel genotypes and phenotypes data. The main aims of precision medicine include early diagnosis, screening, and personalized treatment regime for a patient ba...