AIMC Topic: Humans

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A deep look into radiomics.

La Radiologia medica
Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into ...

Timesias: A machine learning pipeline for predicting outcomes from time-series clinical records.

STAR protocols
The prediction of outcomes is a critical part of the clinical surveillance for hospitalized patients. Here, we present Timesias, a machine learning pipeline which predicts outcomes from real-time sequential clinical data. The strategy implemented in ...

AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning.

Artificial intelligence in medicine
Obstructive Sleep Apnea Syndrome (OSAS) is the most common sleep-related breathing disorder. It is caused by an increased upper airway resistance during sleep, which determines episodes of partial or complete interruption of airflow. The detection an...

Visual comprehension and orientation into the COVID-19 CIDO ontology.

Journal of biomedical informatics
The current intensive research on potential remedies and vaccinations for COVID-19 would greatly benefit from an ontology of standardized COVID terms. The Coronavirus Infectious Disease Ontology (CIDO) is the largest among several COVID ontologies, a...

Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.

Sensors (Basel, Switzerland)
In sport science, athlete tracking and motion analysis are essential for monitoring and optimizing training programs, with the goal of increasing success in competition and preventing injury. At present, contact-free, camera-based, multi-athlete dete...

Diagnostic of Operation Conditions and Sensor Faults Using Machine Learning in Sucker-Rod Pumping Wells.

Sensors (Basel, Switzerland)
In sucker-rod pumping wells, due to the lack of an early diagnosis of operating condition or sensor faults, several problems can go unnoticed. These problems can increase downtime and production loss. In these wells, the diagnosis of operation condit...

Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm.

Sensors (Basel, Switzerland)
One essential step in radiotherapy treatment planning is the organ at risk of segmentation in Computed Tomography (CT). Many recent studies have focused on several organs such as the lung, heart, esophagus, trachea, liver, aorta, kidney, and prostate...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

Scientific reports
With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (...

A deep learning algorithm to translate and classify cardiac electrophysiology.

eLife
The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network ...