AIMC Topic: Female

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Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of : A Pilot Integrative Machine Learning Study.

Depression and anxiety
Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psychiatric disorder associated with suicide; therefore, it is essential to prioritize suicide predicti...

Physical frailty identification using machine learning to explore the 5-item FRAIL scale, Cardiovascular Health Study index, and Study of Osteoporotic Fractures index.

Frontiers in public health
BACKGROUND: Physical frailty is an important issue in aging societies. Three models of physical frailty assessment, the 5-Item fatigue, resistance, ambulation, illness and loss of weight (FRAIL); Cardiovascular Health Study (CHS); and Study of Osteop...

Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.

PloS one
OBJECTIVE: To establish whether or not a natural language processing technique could identify two common inpatient neurosurgical comorbidities using only text reports of inpatient head imaging.

FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data-Study protocol of a multicenter trial.

PloS one
INTRODUCTION: Endometriosis is a chronic disease that affects up to 190 million women and those assigned female at birth and remains unresolved mainly in terms of etiology and optimal therapy. It is defined by the presence of endometrium-like tissue ...

Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of data size and analysis. Therefore, we proposed to develop a deep lea...

Safety and Efficacy of Acute Central Venous Catheters for Hemodialysis with Sodium Bicarbonate versus an Antibiotic Catheter Locking Solution.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
This study was conducted to determine the safety and efficacy of acute central venous catheters (CVC) using a sodium bicarbonate catheter locking solution (SBCLS) versus an antibiotic catheter locking solution (ACLS). Our study included patients aged...

Gender Bias in Artificial Intelligence-Written Letters of Reference.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Letters of reference (LORs) play an important role in postgraduate residency applications. Human-written LORs have been shown to carry implicit gender bias, such as using more agentic versus communal words for men, and more frequent doubt-...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

Theriogenology
This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blood mononuclear cells (PBMCs), CL blood perfusion by Doppler ultrasound (Doppler-US), plasma concentration of P4 on Day 21 and pregnancy-associated gly...

What do you think caused your ALS? An analysis of the CDC national amyotrophic lateral sclerosis patient registry qualitative risk factor data using artificial intelligence and qualitative methodology.

Amyotrophic lateral sclerosis & frontotemporal degeneration
OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is an incurable, progressive neurodegenerative disease with a significant health burden and poorly understood etiology. This analysis assessed the narrative responses from 3,061 participants in the Cente...