AIMC Topic: Female

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Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Science advances
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...

Co-Design of a Health Screening Program Fact Sheet by People Experiencing Homelessness and ChatGPT: Focus Group Study.

JMIR formative research
BACKGROUND: People experiencing homelessness have worse oral health outcomes and a notable health informational asymmetry compared to the general population. Screening programs present a viable option for this population; however, barriers to access,...

The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks.

eLife
Critical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based Hebbian plasticity and homeostatic synaptic scaling a...

Perspectives of Health Care Professionals on the Use of AI to Support Clinical Decision-Making in the Management of Multiple Long-Term Conditions: Interview Study.

Journal of medical Internet research
BACKGROUND: Managing multiple long-term conditions (MLTC) is complex. Clinical management guidelines are typically focused on individual conditions and lack a robust evidence base for patients with MLTC. MLTC management is largely delivered in primar...

Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.

Journal of global health
BACKGROUND: Artificial intelligence (AI) holds significant promise for medical applications, particularly in coronary computed tomography angiography (CTA). We assessed the knowledge, attitudes, and practices (KAP) of cardiovascular health care perso...

Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.

Renal failure
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...

Automatically predicting lung tumor invasiveness using deep neural networks.

Medical engineering & physics
Early lung cancer invasive detection is important for further treatment and saving lives. In clinical practice, lung tumor invasiveness (LTI) detection is very challenging, imaging-based automatic prediction algorithms offer a non-invasive approach. ...

Self-supervised deep metric learning for prototypical zero-shot lesion retrieval in placenta whole-slide images.

Computers in biology and medicine
Postnatal adverse outcomes can often be explained and predicted by the pathological evaluation of the placenta after a pregnancy. However, placenta whole-slide image (WSI) analysis is not performed systematically due to the specialized skills require...

Automatic CNN-based 3D/2D non-rigid registration platform for fast 3D femur reconstruction and clinical 3D measurements from Bi-planar radiographs.

Computers in biology and medicine
PURPOSE: This paper presents an automatic 3D/2D non-rigid registration method for fast 3D reconstruction and clinical measurements of the femur.

Can circadian rhythms of heart rate variability identify major depressive disorder? - A study based on support vector machine analysis.

Asian journal of psychiatry
BACKGROUND: Major depressive disorder (MDD) is a prevalent and severe psychiatric condition for which objective diagnostic tools are lacking. Heart rate variability (HRV), an index of autonomic nervous system (ANS) function, has shown potential for d...