AIMC Topic: Adult

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Use of machine learning to analyse routinely collected intensive care unit data: a systematic review.

Critical care (London, England)
BACKGROUND: Intensive care units (ICUs) face financial, bed management, and staffing constraints. Detailed data covering all aspects of patients' journeys into and through intensive care are now collected and stored in electronic health records: mach...

Applying machine learning to predict future adherence to physical activity programs.

BMC medical informatics and decision making
BACKGROUND: Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured...

Feedback delays can enhance anticipatory synchronization in human-machine interaction.

PloS one
Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has...

Hospital readmissions after limited vs. extended lymph node dissection during open and robot-assisted radical prostatectomy.

Urologic oncology
PURPOSE: Differences exist concerning when and how to perform lymph node dissection (LND) during radical prostatectomy due to lack of high-grade evidence to its safety and efficacy. We aimed to compare readmission rates between limited and extended L...

Real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinoma using a deep learning model (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: We developed a system for computer-assisted diagnosis (CAD) for real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinomas (ESCCs) to assist the diagnosis of esophageal cancer.

Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.

IEEE transactions on medical imaging
ABUS, or Automated breast ultrasound, is an innovative and promising method of screening for breast examination. Comparing to common B-mode 2D ultrasound, ABUS attains operator-independent image acquisition and also provides 3D views of the whole bre...

Machine Learning Diagnosis of Peritonsillar Abscess.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Peritonsillar abscess (PTA) is a difficult diagnosis to make clinically, with clinical examination of even otolaryngologists showing poor sensitivity and specificity. Machine learning is a form of artificial intelligence that "learns" from data to ma...

Predicting sepsis with a recurrent neural network using the MIMIC III database.

Computers in biology and medicine
OBJECTIVE: Predicting sepsis onset with a recurrent neural network and performance comparison with InSight - a previously proposed algorithm for the prediction of sepsis onset.

The Attitudes of Therapists and Physicians on the Use of Sex Robots in Sexual Therapy: Online Survey and Interview Study.

Journal of medical Internet research
BACKGROUND: Various types of robots have already been successfully used in medical care, and the use of new technologies is also playing an increasing role in the area of sexuality. Sex robots are marketed as advanced sex toys and sex dolls with arti...

Characterizing functional regional homogeneity (ReHo) as a B-SNIP psychosis biomarker using traditional and machine learning approaches.

Schizophrenia research
BACKGROUND: Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived using brain-based cognitive and electrophysiological markers. Here, we characterized a local functional-connectivity measure, regional homogeneity (ReH...