AIMC Topic: Adult

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Artificial Intelligence-Assisted Muscular Ultrasonography for Assessing Inflammation and Muscle Mass in Patients at Risk of Malnutrition.

Nutrients
BACKGROUND: Malnutrition, influenced by inflammation, is associated with muscle depletion and body composition changes. This study aimed to evaluate muscle mass and quality using Artificial Intelligence (AI)-enhanced ultrasonography in patients with ...

Mobile health apps for skin cancer triage in the general population: a qualitative study on healthcare providers' perspectives.

BMC cancer
BACKGROUND: Mobile health (mHealth) applications (apps) integrated with artificial intelligence for skin cancer triage are increasingly available to the general public. Nevertheless, their actual uptake is limited. Although endorsement by healthcare ...

Exploring machine learning algorithms to predict short birth intervals and identify its determinants among reproductive-age women in East Africa.

BMC pregnancy and childbirth
BACKGROUND: The occurrence of short birth intervals among reproductive-age women in East Africa is a critical public health issue, contributing to maternal and child health risks. Identifying the key factors that predict short birth intervals can hel...

Multiparameter MRI-based model integrating radiomics and deep learning for preoperative staging of laryngeal squamous cell carcinoma.

Scientific reports
The accurate preoperative staging of laryngeal squamous cell carcinoma (LSCC) provides valuable guidance for clinical decision-making. The objective of this study was to establish a multiparametric MRI model using radiomics and deep learning (DL) to ...

Development of a 5-Year Risk Prediction Model for Transition From Prediabetes to Diabetes Using Machine Learning: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Diabetes has emerged as a critical global public health crisis. Prediabetes, as the transitional phase with 5%-10% annual progression to diabetes, offers a critical window for intervention. The lack of a 5-year risk prediction model for d...

Binary classification of gynecological cancers based on ATR-FTIR spectroscopy and machine learning using urine samples.

Clinical and experimental medicine
Making an early diagnosis of cancer still in the early stages, when completely asymptomatic, is the challenge modern medicine has been setting for several decades. In gynecology, no effective screening has yet been found and approved for endometrial ...

Ultrasound-based deep learning radiomics for enhanced axillary lymph node metastasis assessment: a multicenter study.

The oncologist
BACKGROUND: Accurate preoperative assessment of axillary lymph node metastasis (ALNM) in breast cancer is crucial for guiding treatment decisions. This study aimed to develop a deep-learning radiomics model for assessing ALNM and to evaluate its impa...

Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.

BMJ open
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...

Event-related potentials reveal incongruent behavior of autonomous vehicles in the moral machine dilemma.

Scientific reports
We investigated event-related potentials (ERPs) in the context of autonomous vehicles (AVs)-specifically in ambiguous, morally challenging traffic situations. In our study, participants (n = 34) observed a putative artificial intelligence (AI) making...