AIMC Topic: Humans

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On-Mask Magnetoelastic Sensor Network for Self-Powered Respiratory Monitoring.

ACS nano
Respiratory monitoring is crucial because it provides key insights into a person's health and physiological conditions. Conventional respiratory sensing is significantly challenged by the presence of water vapor in exhaled breath. An on-mask magnetoe...

Noninvasive real-time monitoring of cellular spatiotemporal dynamics via machine learning-enhanced electrical impedance spectroscopy.

Science advances
Monitoring cellular spatiotemporal dynamics is essential for understanding complex biological processes such as organ development and cancer progression. Using live-cell fluorescence microscopy to track cellular dynamics is often limited by dye-induc...

Innovative organ-on-a-chip platforms for exploring tumorigenesis and therapy in head and neck cancer.

Journal of translational medicine
BACKGROUND: Head and neck cancer (HNC) presents significant research challenges due to the complexity of its tumor microenvironment (TME) and the heterogeneity across different cancer subtypes. Recent advancements in three-dimensional (3D) culture mo...

Artificial intelligence for diagnosing rare bone diseases: a global survey of healthcare professionals.

Orphanet journal of rare diseases
BACKGROUND: Rare bone diseases (RBDs) are an important group of conditions characterized by abnormalities in bone and cartilage. Their large number, individual rarity, and heterogeneity make accurate and timely diagnosis challenging. Establishing cor...

Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization.

BMC medical informatics and decision making
BACKGROUND: This study aims to address the gap in understanding clinicians' attitudes toward explainable AI (XAI) methods applied to machine learning models using tabular data, commonly found in clinical settings. It specifically explores clinicians'...

Knowledge and perception of artificial lntelligence education among undergraduate healthcare students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is gaining recognition for its ability to enhance patient outcomes in healthcare. Therefore, integrating AI into the undergraduate curriculum is essential to equip students with foundational knowledge before g...

Screening for endometriosis: A scoping review of screening measures that could support early diagnosis.

BMC women's health
BACKGROUND: Endometriosis is prevalent in approximately 6-10% of all women of reproductive age and is associated with pelvic pain, heavy menstrual bleeding, infertility, and pain during intercourse. Despite reporting symptoms, women wait around 11 ye...

Comparative study of 2D vs. 3D AI-enhanced ultrasound for fetal crown-rump length evaluation in the first trimester.

BMC pregnancy and childbirth
BACKGROUND: Accurate fetal growth evaluation is crucial for monitoring fetal health, with crown-rump length (CRL) being the gold standard for estimating gestational age and assessing growth during the first trimester. To enhance CRL evaluation accura...

A novel machine learning architecture to improve classification of intermediate cases in health: workflow and case study for public health.

BMC bioinformatics
BACKGROUND: The practice of medicine has evolved significantly during the past decade, with the emergence of Machine Learning (ML) that offers the opportunity of personalized patient-tailored care. However, ML models still face some challenges when c...

Conditional GAN performs better than orthopedic surgeon in virtual reduction of femoral neck fracture.

BMC musculoskeletal disorders
OBJECTIVE: Satisfied reduction of fracture is hard to achieve. The purpose of this study is to develop a virtual fracture reduction technique using conditional GAN (Generative Adversarial Network), and evaluate its performance in simulating and guidi...