AIMC Topic: Female

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Designing a deep hybridized residual and SE model for MRI image-based brain tumor prediction.

Journal of clinical ultrasound : JCU
Deep learning techniques have become crucial in the detection of brain tumors but classifying numerous images is time-consuming and error-prone, impacting timely diagnosis. This can hinder the effectiveness of these techniques in detecting brain tumo...

Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text su...

Boosting predictive models and augmenting patient data with relevant genomic and pathway information.

Computers in biology and medicine
The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models,...

Classifying early infant feeding status from clinical notes using natural language processing and machine learning.

Scientific reports
The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classi...

Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database.

Diabetes & metabolic syndrome
AIM: To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

PloS one
Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and ac...

Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.

Clinical research in cardiology : official journal of the German Cardiac Society
BACKGROUND: Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for identifying such patients are difficult to implement in electronic health record (EHR) systems.

Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
OBJECTIVES: Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated.

Dynamics of changes in broiler spatial distribution induced by a robot with autonomous navigation along the growing cycle.

Poultry science
Welfare problems in broiler chickens are associated with accelerated growth in high density and barren environments. Encouraging broiler movement yields benefits by increasing locomotion, foraging, and environmental exploration. Robot sensors with au...