AIMC Topic: Female

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Examining worry and secondary stressors on grief severity using machine learning.

Anxiety, stress, and coping
BACKGROUND & OBJECTIVES: Worry and loss-related secondary stressors appear to be important correlates of problematic grief responses. However, the relative importance of these variables in the context of established correlates of grief responding, ra...

Machine learning identifies clusters of the normal adolescent spine based on sagittal balance.

Spine deformity
PURPOSE: This study applied a machine learning semi-supervised clustering approach to radiographs of adolescent sagittal spines from a single pediatric institution to identify patterns of sagittal alignment in the normal adolescent spine. We sought t...

Prediction of 90 day readmission in heart failure with preserved ejection fraction by interpretable machine learning.

ESC heart failure
AIMS: Certain critical risk factors of heart failure with preserved ejection fraction (HFpEF) patients were significantly different from those of heart failure with reduced ejection fraction (HFrEF) patients, resulting in the limitations of existing ...

Machine learning-based reproducible prediction of type 2 diabetes subtypes.

Diabetologia
AIMS/HYPOTHESIS: Clustering-based subclassification of type 2 diabetes, which reflects pathophysiology and genetic predisposition, is a promising approach for providing personalised and effective therapeutic strategies. Ahlqvist's classification is c...

Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research.

Applied psychology. Health and well-being
Demystifying machine learning (ML) approaches through the synergy of psychology and artificial intelligence can achieve a balance between predictive and explanatory power in model development while enhancing rigor in validation and reporting standard...

Accurate diagnosis of acute appendicitis in the emergency department: an artificial intelligence-based approach.

Internal and emergency medicine
The diagnosis of abdominal pain in emergency departments is challenging, and appendicitis is a common concern. Atypical symptoms often delay diagnosis. Although the Alvarado score aids in decision-making, its low specificity can lead to unnecessary s...

An efficient ANN SoC for detecting Alzheimer's disease based on recurrent computing.

Computers in biology and medicine
Alzheimer's Disease (AD) is an irreversible, degenerative condition that, while incurable, can have its progression slowed or impeded. While there are numerous methods utilizing neural networks for AD detection, there is a scarcity of High-performanc...

Establishment and validation of a risk stratification model for stroke risk within three years in patients with cerebral small vessel disease using a combined MRI and machine learning algorithm.

SLAS technology
BACKGROUND: Cerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a...

Determinants of adoption of household water treatment in Haiti using two analysis methods: logistic regression and machine learning.

Journal of water and health
Household water treatment (HWT) is recommended when safe drinking water is limited. To understand determinants of HWT adoption, we conducted a cross-sectional survey with 650 households across different regions in Haiti. Data were collected on 71 dem...

Machine learning allows expert level classification of intraoperative motor evoked potentials during neurosurgical procedures.

Computers in biology and medicine
OBJECTIVE: To develop and evaluate machine learning (ML) approaches for muscle identification using intraoperative motor evoked potentials (MEPs), and to compare their performance to human experts.