AIMC Topic: Humans

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Novel anoikis-related diagnostic biomarkers for aortic dissection based on machine learning.

Scientific reports
Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is characterized by acute onset and poor prognosis, while the pathogenesis of AD is still unclear and may affect or even delay the diagnosis of AD. Ancho...

Decoding of pain during heel lancing in human neonates with EEG signal and machine learning approach.

Scientific reports
Currently, pain assessment using electroencephalogram signals and machine learning methods in clinical studies is of great importance, especially for those who cannot express their pain. Since newborns are among the high-risk group and always experie...

Early prediction of functional impairment at hospital discharge in patients with osteoporotic vertebral fracture: a machine learning approach.

Scientific reports
Although conservative treatment is commonly used for osteoporotic vertebral fracture (OVF), some patients experience functional disability following OVF. This study aimed to develop prediction models for new-onset functional impairment following admi...

Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.

Scientific reports
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based...

BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.

Scientific data
In the past several years, a few cervical Pap smear datasets have been published for use in clinical training. However, most publicly available datasets consist of pre-segmented single cell images, contain on-image annotations that must be manually e...

Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

BMC medical education
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning ...

The aluminum standard: using generative Artificial Intelligence tools to synthesize and annotate non-structured patient data.

BMC medical informatics and decision making
BACKGROUND: Medical narratives are fundamental to the correct identification of a patient's health condition. This is not only because it describes the patient's situation. It also contains relevant information about the patient's context and health ...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BMC public health
BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population healt...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

BMC genomics
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the func...

Multiomics integration and machine learning reveal prognostic programmed cell death signatures in gastric cancer.

Scientific reports
Gastric cancer (GC) is characterized by notable heterogeneity and the impact of molecular subtypes on treatment and prognosis. The role of programmed cell death (PCD) in cellular processes is critical, yet its specific function in GC is underexplored...