AIMC Topic: Humans

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Identification and analysis of pyroptosis-related key genes in heart failure.

Journal of cardiothoracic surgery
BACKGROUND: Pyroptosis plays a pivotal role in the pathogenesis of Heart Failure (HF). However, the current understanding of how pyroptosis-related genes (PRGs) influence HF is scarce. This study aimed to explore the link between PRGs and HF based on...

Evolving role of point-of-care ultrasound in prehospital emergency care: a narrative review.

Scandinavian journal of trauma, resuscitation and emergency medicine
Point-of-care ultrasound is an emerging technology in prehospital emergency care, covering a wide range of medical and traumatic disease patterns. As an ad-hoc imaging modality, it is performed on-scene and during ground or aeromedical transport, ena...

Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study.

Critical care (London, England)
BACKGROUND: The current Surviving Sepsis Campaign (SSC) guidelines provide recommendations on timing of administering antibiotics in sepsis patients based on probability of sepsis and presence of shock. However, there have been minimal efforts to str...

A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study.

World journal of emergency surgery : WJES
BACKGROUND: Accurately identifying difficult laparoscopic cholecystectomy (DLC) preoperatively remains a clinical challenge. Previous studies utilizing clinical variables or morphological imaging markers have demonstrated suboptimal predictive perfor...

Advancing shock prediction: leveraging prior knowledge and self-controlled data for enhanced model accuracy and generalizability.

BMC medical informatics and decision making
OBJECTIVES: Timely intervention in shock is vital, as delays over one hour greatly increase mortality. This study aims to develop an enhanced machine learning model that improves predictive performance by utilizing self-controlled data and applying f...

Characterizing individual and methodological risk factors for survey non-completion using machine learning: findings from the U.S. Millennium Cohort Study.

BMC medical research methodology
BACKGROUND: Missing survey data can threaten the validity and generalizability of findings from longitudinal cohort studies. Respondent characteristics and survey attributes may contribute to patterns of survey non-completion, a form of missing data ...

Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.

BMC cancer
BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organization (WHO) grade 4 Central Nervous System (CNS) gliomas is highly relevant for prognostic stratification and personalized treatment.

Advances in nanorobotics for gastrointestinal surgery: a new frontier in precision medicine and minimally invasive therapeutics.

Journal of robotic surgery
Nanorobotics is catalyzing a paradigm shift in GI surgery by synergizing nanoscale engineering, synthetic biology, and intelligent computation to create a novel frontier in precision medicine. This review critically discusses the most recent experime...

A hybrid learning approach for MRI-based detection of alzheimer's disease stages using dual CNNs and ensemble classifier.

Scientific reports
Alzheimer's Disease (AD) and related dementias are significant global health issues characterized by progressive cognitive decline and memory loss. Computer-aided systems can help physicians in the early and accurate detection of AD, enabling timely ...

An iterative strategy to design 4-1BB agonist nanobodies de novo with generative AI models.

Scientific reports
The 4-1BB receptor, a key member of the tumor necrosis factor receptor (TNFR) family, represents a highly promising target for cancer immunotherapy. In this study, we developed a novel in silico pipeline to design VHH domain antibodies targeting 4-1B...