AIMC Topic: Humans

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Early neoplastic lesions of the pancreas: initiation, progression, and opportunities for precancer interception.

The Journal of clinical investigation
Pancreatic ductal adenocarcinoma (PDAC) is known to progress from one of two main precursor lesions: pancreatic intraepithelial neoplasia (PanIN) or intraductal papillary mucinous neoplasm (IPMN). The poor survival rates for patients with PDAC, even ...

The Application of Artificial Intelligence in Addressing Biothreats.

Disaster medicine and public health preparedness
The advent of new technologies, particularly artificial intelligence (AI), has expanded the array of options and enhanced performance in addressing biothreats. This article provides a comprehensive overview of the specific applications of AI in addre...

BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.

BMC biology
BACKGROUND: Diabetes is a global metabolic disease that urgently calls for the development of new and effective therapeutic agents. Anti-diabetic peptides (ADPs) have emerged as a research hotspot due to their therapeutic potential and natural safety...

Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department.

BMC emergency medicine
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...

Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.

BMC gastroenterology
OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic fatty liver disease (NAFLD) using the random survival forests (RSF), and to investigate the distribution of NAFLD risk with time.

Exploring novel molecular mechanisms underlying recurrent pregnancy loss in decidual tissues.

Scientific reports
Recurrent pregnancy loss (RPL), which affects approximately 2.5% of reproductive-aged women, remains idiopathic in more than 50% of cases, necessitating mechanistic insights and biomarkers. Three RPL decidual tissue transcriptomic datasets (GSE113790...

Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients.

Scientific reports
Following complete mesocolic excision (CME), heart failure (HF) emerges as a significant complication, exerting substantial impacts on both short-term and long-term patient prognoses. The primary objective of our investigation was to develop a machin...

Personalizing brain stimulation: continual learning for sleep spindle detection.

Journal of neural engineering
Personalized stimulation, in which algorithms used to detect neural events adapt to a user's unique neural characteristics, may be crucial to enable optimized and consistent stimulation quality for both fundamental research and clinical applications....

Applying binary mixed model to predict knee osteoarthritis pain.

PloS one
Data used to understand knee osteoarthritis (KOA) often involves knee-level, rather than person-level information. Failure to account for the correlation between joints within a person may lead to inaccurate inferences. The aim of this study was to d...

Identification and experimental validation of BMX as a crucial PANoptosis‑related gene for immune response in Spinal Cord Injury.

PloS one
Spinal cord injury (SCI) is a debilitating neurological condition that severely impacts motor, sensory, and autonomic functions, leading to significant challenges in patient quality of life and imposing substantial economic burdens on society. PANopt...