AIMC Topic: Female

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Representation of locomotive action affordances in human behavior, brains, and deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America
To decide how to move around the world, we must determine which locomotive actions (e.g., walking, swimming, or climbing) are afforded by the immediate visual environment. The neural basis of our ability to recognize locomotive affordances is unknown...

Microbial dysbiosis and its diagnostic potential in androgenetic alopecia: insights from multi-kingdom sequencing and machine learning.

mSystems
Androgenetic alopecia (AGA), the most common form of hair loss, has been linked to dysbiosis of the scalp microbiome. In this study, we collected microbiome samples from the frontal baldness and occipital regions of patients with varying stages of AG...

Machine Learning Prediction of Pancreatitis Risk With Antithyroid Drugs: A Nationwide Retrospective Observational Study.

The Journal of clinical endocrinology and metabolism
BACKGROUND: In recent years, there has been increasing data showing that the risk of acute pancreatitis (AP) is increased in patients using methimazole (MMI). The aim of this population-based study was to investigate the association between drugs use...

Imaging-Based AI for Predicting Lymphovascular Space Invasion in Cervical Cancer: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: The role of artificial intelligence (AI) in enhancing the accuracy of lymphovascular space invasion (LVSI) detection in cervical cancer remains debated.

Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb.

JMIR cancer
Digital health interventions offer promise for scalable and accessible health care, but access is still limited by some participatory challenges, especially for disadvantaged families facing limited health literacy, language barriers, low income, or ...

Antimicrobial peptide developed with machine learning sequence optimization targets drug resistant Staphylococcus aureus in mice.

The Journal of clinical investigation
As antimicrobial resistance rises, new antibacterial candidates are urgently needed. Using sequence space information from over 14,743 functional antimicrobial peptides (AMPs), we improved the antimicrobial properties of citropin 1.1, an AMP with wea...

Beyond the Posts: Analyzing Breast Implant Illness Discourse With Natural Language Processing and Deep Learning.

Aesthetic surgery journal
BACKGROUND: Breast implant illness (BII) is a spectrum of symptoms some people attribute to breast implants. Although causality remains unproven, patient interest has grown significantly. Understanding patient perceptions of BII on social media is cr...

Artificial Intelligence for Patient Support: Assessing Retrieval-Augmented Generation for Answering Postoperative Rhinoplasty Questions.

Aesthetic surgery journal
BACKGROUND: Although artificial intelligence (AI) is revolutionizing healthcare, inaccurate or incomplete information from pretrained large language models (LLMs) like ChatGPT poses significant risks to patient safety. Retrieval-augmented generation ...

AI-powered evaluation of lung function for diagnosis of interstitial lung disease.

Thorax
BACKGROUND: The diagnosis of interstitial lung disease (ILD) can pose a challenge as the pulmonary function test (PFT) is only minimally affected at the onset. To improve early diagnosis, this study aims to explore the potential of artificial intelli...

Pioneering artificial intelligence-based real time assistance for intracranial liquid embolization in humans: an initial experience.

Journal of neurointerventional surgery
BACKGROUND: Liquid embolization in neuroendovascular procedures carries the risk of embolizing an inappropriate vessel. Operators must pay close attention to multiple vessels during the procedure to avoid ischemic complications. We report our experie...