AIMC Topic: Humans

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Greedy based convolutional neural network optimization for detecting apnea.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Sleep apnea is a common sleep disorder, usually diagnosed using an expensive, highly specialized, and inconvenient test called polysomnography. A single SpO2 sensor based on an automated classification system can be develope...

Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.

International journal of radiation oncology, biology, physics
PURPOSE: To investigate machine segmentation of pelvic anatomy in magnetic resonance imaging (MRI)-assisted radiosurgery (MARS) for prostate cancer using prostate brachytherapy MRIs acquired with different pulse sequences and image contrasts.

Ischemia and outcome prediction by cardiac CT based machine learning.

The international journal of cardiovascular imaging
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for card...

Using the VQ-VAE to improve the recognition of abnormalities in short-duration 12-lead electrocardiogram records.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Morphological diagnosis is a basic clinical task of the short-duration 12-lead electrocardiogram (ECG). Due to the scarcity of positive samples and other factors, there is currently no algorithm that is comparable to human e...

Personalized connectome fingerprints: Their importance in cognition from childhood to adult years.

NeuroImage
Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a pe...

A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiomics for stage T3N1M0 nasopharyngeal carcinoma (NPC) patients receiving induction chemotherapy (ICT) prior to concurrent chemoradiotherapy (CCRT).

Detecting caries lesions of different radiographic extension on bitewings using deep learning.

Journal of dentistry
OBJECTIVES: We aimed to apply deep learning to detect caries lesions of different radiographic extension on bitewings, hypothesizing it to be significantly more accurate than individual dentists.

Single-port transoral robotic combined approach with sialendoscopy for sialolithiasis: Case report and review of the literature.

Head & neck
BACKGROUND: The da Vinci single-port (SP) is utilized in transoral robotic surgery (TORS) procedures for malignant oropharyngeal tumors. We report a case utilizing the da Vinci SP in TORS for sialolith removal.

An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram.

Sensors (Basel, Switzerland)
The invasive method of fetal electrocardiogram (fECG) monitoring is widely used with electrodes directly attached to the fetal scalp. There are potential risks such as infection and, thus, it is usually carried out during labor in rare cases. Recent ...

Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses.

Diagnostic pathology
BACKGROUND: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with wh...