AIMC Topic: Humans

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A Tiny Matched Filter-Based CNN for Inter-Patient ECG Classification and Arrhythmia Detection at the Edge.

Sensors (Basel, Switzerland)
Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized for arrhythmia detection. Contemporary ML algorithms are typically deployed on the cloud, which may not always meet the availability and privacy requ...

Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach.

BMC medical informatics and decision making
BACKGROUND: Extracting relevant information about infectious diseases is an essential task. However, a significant obstacle in supporting public health research is the lack of methods for effectively mining large amounts of health data.

An intelligent medical guidance and recommendation model driven by patient-physician communication data.

Frontiers in public health
Based on the online patient-physician communication data, this study used natural language processing and machine learning algorithm to construct a medical intelligent guidance and recommendation model. First, based on 16,935 patient main complaint d...

Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database.

PloS one
INTRODUCTION: Many researchers used machine learning (ML) to predict the prognosis of breast cancer (BC) patients and noticed that the ML model had good individualized prediction performance.

Early recognition of risk of critical adverse events based on deep neural decision gradient boosting.

Frontiers in public health
INTRODUCTION: Perioperative critical events will affect the quality of medical services and threaten the safety of patients. Using scientific methods to evaluate the perioperative risk of critical illness is of great significance for improving the qu...

A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals.

Disability and rehabilitation. Assistive technology
PURPOSE: This study proposes a concept for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) based on artificial intelligence (AI) using physiological and motion signals.

Research of intent recognition in rehabilitation robots: a systematic review.

Disability and rehabilitation. Assistive technology
PURPOSE: Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with intent recognition have been developed by academic institutions and commercial companies. However, there...

Effect of Contrast Level and Image Format on a Deep Learning Algorithm for the Detection of Pneumothorax with Chest Radiography.

Journal of digital imaging
Under the black-box nature in the deep learning model, it is uncertain how the change in contrast level and format affects the performance. We aimed to investigate the effect of contrast level and image format on the effectiveness of deep learning fo...

Improved neural network for predicting blood donations based on two emergent factors.

Transfusion clinique et biologique : journal de la Societe francaise de transfusion sanguine
BACKGROUND: Blood donation forecasting is a critical part of blood supply chain management. However, few studies have focused on modeling blood donation with different emergency factors. The purpose of this study was to investigate the effects of dif...