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Identifying smart technology and artificial intelligence solutions for human factors and ergonomic challenges in all-hazard response: A survey study.

Applied ergonomics
Emergency responders face significant human factors and ergonomic (HF/E) challenges related to physical, cognitive, emotional, and training demands during high-stress situations. This study investigates these issues through a survey of 60 emergency r...

ABVS breast tumour segmentation via integrating CNN with dilated sampling self-attention and feature interaction Transformer.

Neural networks : the official journal of the International Neural Network Society
Given the rapid increase in breast cancer incidence, the Automated Breast Volume Scanner (ABVS) is developed to screen breast tumours efficiently and accurately. However, reviewing ABVS images is a challenging task owing to the significant variations...

MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.

Shock (Augusta, Ga.)
Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and mortality. Machine learning (ML), combined with parameters such as shock indices, can potentially imp...

EVALUATION OF PROGNOSTIC RISK MODELS BASED ON AGE AND COMORBIDITY IN SEPTIC PATIENTS: INSIGHTS FROM MACHINE LEARNING AND TRADITIONAL METHODS IN A LARGE-SCALE, MULTICENTER, RETROSPECTIVE STUDY.

Shock (Augusta, Ga.)
Background: Age and comorbidity significantly impact the prognosis of septic patients and inform treatment decisions. To provide clinicians with effective tools for identifying high-risk patients, this study assesses the predictive value of the age-a...

CHRONIC CRITICAL ILLNESS IN BONE TRAUMA PATIENTS: AN AI-BASED APPROACH FOR INTENSIVE CARE UNIT HEALTHCARE PROVIDERS.

Shock (Augusta, Ga.)
Background: Chronic critical illness (CCI) is a serious condition characterized by a prolonged course of illness, resulting in elevated morbidity and mortality. CCI presents significant challenges for healthcare providers in intensive care units (ICU...

Predicting treatment outcome in congenital adrenal hyperplasia using urine steroidomics and machine learning.

European journal of endocrinology
OBJECTIVE: Treatment monitoring of individuals with congenital adrenal hyperplasia (CAH) remains unsatisfactory. Comprehensive 24 h urine steroid profiling provides detailed insight into adrenal steroid pathways. We investigated whether 24 h urine st...

Derivation and validation of an artificial intelligence-based plaque burden safety cut-off for long-term acute coronary syndrome from coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging
AIMS: Artificial intelligence (AI) has enabled accurate and fast plaque quantification from coronary computed tomography angiography (CCTA). However, AI detects any coronary plaque in up to 97% of patients. To avoid overdiagnosis, a plaque burden saf...

Hybrid strategy of coronary atherosclerosis characterization with T1-weighted MRI and CT angiography to non-invasively predict periprocedural myocardial injury.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) can predict periprocedural myocardial injury (PMI) after percutaneous coronary intervention (PCI). We aimed to investigate whether integrating MRI with CCTA, u...

Reproductive health and the Vatican.

African journal of reproductive health
Following the repositioning of the Holy See on diverse issues, it is now expected that Pope Leo XIV will further advance policies pertaining to sexual and reproductive health. The role of regional and local interpretation of global policies, whether ...