AI Medical Compendium Topic:
Models, Theoretical

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A proposed soft pneumatic actuator control based on angle estimation from data-driven model.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This article proposes a bending angle controller for soft pneumatic actuators, which could be implemented in soft robotic rehabilitation gloves to assist patients with hand impairment, such as stroke survivors. A data-driven model is used to estimate...

Automatic Seizure Detection using Fully Convolutional Nested LSTM.

International journal of neural systems
The automatic seizure detection system can effectively help doctors to monitor and diagnose epilepsy thus reducing their workload. Many outstanding studies have given good results in the two-class seizure detection problems, but most of them are base...

Machine Learning in Drug Discovery and Development Part 1: A Primer.

CPT: pharmacometrics & systems pharmacology
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and develop...

Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils.

Ecotoxicology and environmental safety
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...

Early prediction of circulatory failure in the intensive care unit using machine learning.

Nature medicine
Intensive-care clinicians are presented with large quantities of measurements from multiple monitoring systems. The limited ability of humans to process complex information hinders early recognition of patient deterioration, and high numbers of monit...

Deep learning models for electrocardiograms are susceptible to adversarial attack.

Nature medicine
Electrocardiogram (ECG) acquisition is increasingly widespread in medical and commercial devices, necessitating the development of automated interpretation strategies. Recently, deep neural networks have been used to automatically analyze ECG tracing...

A Hybrid PSO-SVM Model Based on Safety Risk Prediction for the Design Process in Metro Station Construction.

International journal of environmental research and public health
Incorporating safety risk into the design process is one of the most effective design sciences to enhance the safety of metro station construction. In such a case, the concept of Design for Safety (DFS) has attracted much attention. However, most of ...

Parametric generation of three-dimensional gait for robot-assisted rehabilitation.

Biology open
For robot-assisted rehabilitation and assessment of patients with motor dysfunction, the parametric generation of their normal gait as the input for the robot is essential to match with the features of the patient to a greater extent. In addition, th...

Bootstrapping Adversarial Learning of Biomedical Ontology Alignments.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Learning how to automatically align biomedical ontologies has been a long-standing goal, given their ever-growing content and the many applications that rely on them. Because the knowledge graphs underlying biomedical ontologies enable neural learnin...

Interpretation of machine learning predictions for patient outcomes in electronic health records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Electronic health records are an increasingly important resource for understanding the interactions between patient health, environment, and clinical decisions. In this paper we report an empirical study of predictive modeling of seven patient outcom...