AIMC Topic: Humans

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Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.

Biomedical engineering online
BACKGROUND: Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is requ...

Robust brain tumor classification by fusion of deep learning and channel-wise attention mode approach.

BMC medical imaging
Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists' expertise and interpretive skills. However, the advent of deep learning methodologies has revolutionized the field, offering more accurate and effici...

Prediction of short-term progression of COVID-19 pneumonia based on chest CT artificial intelligence: during the Omicron epidemic.

BMC infectious diseases
BACKGROUND AND PURPOSE: The persistent progression of pneumonia is a critical determinant of adverse outcomes in patients afflicted with COVID-19. This study aimed to predict personalized COVID-19 pneumonia progression between the duration of two wee...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Scientific reports
Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies. We attempted to utilize machine learning (ML) using basic pre-labor clinical data...

An explanatory study of factors influencing engagement in AI education at the K-12 Level: an extension of the classic TAM model.

Scientific reports
Artificial intelligence (AI) holds immense promise for K-12 education, yet understanding the factors influencing students' engagement with AI courses remains a challenge. This study addresses this gap by extending the technology acceptance model (TAM...

Highly accurate carbohydrate-binding site prediction with DeepGlycanSite.

Nature communications
As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems a...

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Translational psychiatry
Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention ha...

Study of machine learning techniques for outcome assessment of leptospirosis patients.

Scientific reports
Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise cl...

CACSNet for automatic robust classification and segmentation of carotid artery calcification on panoramic radiographs using a cascaded deep learning network.

Scientific reports
Stroke is one of the major causes of death worldwide, and is closely associated with atherosclerosis of the carotid artery. Panoramic radiographs (PRs) are routinely used in dental practice, and can be used to visualize carotid artery calcification (...

Deep learning-based classification of erosion, synovitis and osteitis in hand MRI of patients with inflammatory arthritis.

RMD open
OBJECTIVES: To train, test and validate the performance of a convolutional neural network (CNN)-based approach for the automated assessment of bone erosions, osteitis and synovitis in hand MRI of patients with inflammatory arthritis.