AIMC Topic: Humans

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Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder.

BMC medical informatics and decision making
BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but may be captured in unstructured clinical notes. Natural language processing (NLP) techniques may be u...

Exploring the role of moxibustion robots in teaching: a cross-sectional study.

BMC medical education
BACKGROUND: Artificial intelligence has gradually been used into various fields of medical education at present. Under the background of moxibustion robot teaching assistance, the study aims to explore the relationship and the internal mechanism betw...

Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.

BMC medical imaging
BACKGROUND: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. L...

Artificial intelligence performance in ultrasound-based lymph node diagnosis: a systematic review and meta-analysis.

BMC cancer
BACKGROUND AND OBJECTIVES: Accurate classification of lymphadenopathy is essential for determining the pathological nature of lymph nodes (LNs), which plays a crucial role in treatment selection. The biopsy method is invasive and carries the risk of ...

MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.

BMC bioinformatics
BACKGROUND: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experi...

Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BMC cancer
BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-invasive imaging technique, aids in melanoma detection but can be limited by subjective interpretati...

Blood cancer prediction model based on deep learning technique.

Scientific reports
Blood cancer is among the critical health concerns among people around the world and normally emanates from genetic and environmental issues. Early detection becomes essential, as the rate of death associated with it is high, to ensure that the rate ...

Hierarchical graph-based integration network for propaganda detection in textual news articles on social media.

Scientific reports
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based mode...

Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data.

Scientific reports
This study aimed to develop an artificial intelligence (AI) model for the screening of degenerative joint disease (DJD) using temporomandibular joint (TMJ) panoramic radiography and joint noise data. A total of 2631 TMJ panoramic images were collecte...

Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders.

Scientific reports
Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivit...