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A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

PloS one
BACKGROUND: AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the 'big data' aggregated from Internet search engines, which contain users' information on the ...

Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

Seizure
PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients ...

Active Inference in OpenAI Gym: A Paradigm for Computational Investigations Into Psychiatric Illness.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Artificial intelligence has recently attained humanlike performance in a number of gamelike domains. These advances have been spurred by brain-inspired architectures and algorithms such as hierarchical filtering and reinforcement learning...

Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non-small-cell lung cancer treated with stereotactic body radiation therapy.

Journal of applied clinical medical physics
BACKGROUND AND PURPOSE: Chest wall toxicity is observed after stereotactic body radiation therapy (SBRT) for peripherally located lung tumors. We utilize machine learning algorithms to identify toxicity predictors to develop dose-volume constraints.

A sequence-to-sequence model-based deep learning approach for recognizing activity of daily living for senior care.

Journal of biomedical informatics
Ensuring the health and safety of independent-living senior citizens is a growing societal concern. Researchers have developed sensor based systems to monitor senior citizens' Activity of Daily Living (ADL), a set of daily activities that can indicat...

A Depth Evidence Score Fusion Algorithm for Chinese Medical Intelligence Question Answering System.

Journal of healthcare engineering
Question answering (QA) system is becoming the focus of the research in medical health in terms of providing fleetly accurate answers to users. Numerous traditional QA systems are faced to simple factual questions and do not obtain accurate answers f...

Deep Endoscopic Visual Measurements.

IEEE journal of biomedical and health informatics
Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body structures, and their application is rapidly extending to cover the increasing needs for accurate therapeutic interventions. In this context, it is ess...

Predicting Athlete Ground Reaction Forces and Moments From Spatio-Temporal Driven CNN Models.

IEEE transactions on bio-medical engineering
The accurate prediction of three-dimensional (3-D) ground reaction forces and moments (GRF/Ms) outside the laboratory setting would represent a watershed for on-field biomechanical analysis. To extricate the biomechanist's reliance on ground embedded...

Deep learning for detection of focal epileptiform discharges from scalp EEG recordings.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Visual assessment of the EEG still outperforms current computer algorithms in detecting epileptiform discharges. Deep learning is a promising novel approach, being able to learn from large datasets. Here, we show pilot results of detecting...

Artificial intelligence outperforms experienced nephrologists to assess dry weight in pediatric patients on chronic hemodialysis.

Pediatric nephrology (Berlin, Germany)
BACKGROUND: Dry weight is the lowest weight patients on hemodialysis can tolerate; correct dry weight estimation is necessary to minimize morbi-mortality, but is difficult to achieve. Here, we used artificial intelligence to improve the accuracy of d...
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