AIMC Topic: Humans

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A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer.

Scientific data
The success of training computer-vision models heavily relies on the support of large-scale, real-world images with annotations. Yet such an annotation-ready dataset is difficult to curate in pathology due to the privacy protection and excessive anno...

Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

BioMed research international
As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the globe. The ability to predictably diagnose viral infections improves the provision of good healthcare as...

Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer.

Oxidative medicine and cellular longevity
So far, it has been reached the academic consensus that the molecular subtypes are via genomic heterogeneity and immune infiltration patterns. Considering that oxidative stress (OS) is involved in tumorigenesis and prognosis prediction, we propose an...

[Not Available].

Canadian journal of surgery. Journal canadien de chirurgie

Deep learning on graphs for multi-omics classification of COPD.

PloS one
Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). However despite recent advances, we remain limited in our ability to incorporate protein-protein inte...

Diagnosis of gastric cancer based on hybrid genes selection approach.

Biotechnology & genetic engineering reviews
Gastric cancer (GC) is the third leading cause of cancer death worldwide. In the field of medicine, machine learning is widely used in genetic data mining and the construction of diagnostic models. This study proposed an intelligent model DERFS-XGBoo...

Can convolutional neural networks identify external carotid artery calcifications?

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcifications (ECACs) in cone beam computed tomography scans.

Accuracy of Information and References Using ChatGPT-3 for Retrieval of Clinical Radiological Information.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To assess the accuracy of answers provided by ChatGPT-3 when prompted with questions from the daily routine of radiologists and to evaluate the text response when ChatGPT-3 was prompted to provide references for a given answer. ChatGPT-3 (San Franc...

Deep Learning Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Vessels encapsulating tumor cluster (VETC) is a critical prognostic factor and therapeutic predictor of hepatocellular carcinoma (HCC). However, noninvasive evaluation of VETC remains challenging.