AIMC Topic: Humans

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Deep learning model for tongue cancer diagnosis using endoscopic images.

Scientific reports
In this study, we developed a deep learning model to identify patients with tongue cancer based on a validated dataset comprising oral endoscopic images. We retrospectively constructed a dataset of 12,400 verified endoscopic images from five universi...

A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system.

Scientific reports
Automated classification and detection of brain abnormalities like a tumor(s) in reconstructed microwave (RMW) brain images are essential for medical application investigation and monitoring disease progression. This paper presents the automatic clas...

Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.

BMC medical informatics and decision making
BACKGROUND: There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) comp...

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

Trials
BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboembolic prophylaxis plays an essential role in AF therapy, but at present, general practitioners (GPs) are presumed to lack the knowledge and enthusias...

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...

Artificial Intelligence Radiotherapy Planning: Automatic Segmentation of Human Organs in CT Images Based on a Modified Convolutional Neural Network.

Frontiers in public health
OBJECTIVE: Precise segmentation of human organs and anatomic structures (especially organs at risk, OARs) is the basis and prerequisite for the treatment planning of radiation therapy. In order to ensure rapid and accurate design of radiotherapy trea...

Detection and Classification of Colorectal Polyp Using Deep Learning.

BioMed research international
Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous...

U-Net-Based Medical Image Segmentation.

Journal of healthcare engineering
Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the perfo...

Key Feature Extraction Method of Electroencephalogram Signal by Independent Component Analysis for Athlete Selection and Training.

Computational intelligence and neuroscience
Emotion is an important expression generated by human beings to external stimuli in the process of interaction with the external environment. It affects all aspects of our lives all the time. Accurate identification of human emotional states and furt...

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.

Computational intelligence and neuroscience
An active research area where the experts from the medical field are trying to envisage the problem with more accuracy is diabetes prediction. Surveys conducted by WHO have shown a remarkable increase in the diabetic patients. Diabetes generally rema...