AIMC Topic: Middle Aged

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Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a machine learning model that can accurately predict the efficacy of HIFU ablation for UFs, assisting t...

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

The Journal of dermatological treatment
BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.

Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM.

Annals of medicine
BACKGROUND: Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associated with an unfavourable prognosis. Therefore, timely diagnosis of LC in CHB patients is crucial.

Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.

Gut microbes
Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between the functional capacity of gut microbiota and their host remains elusive for DKD. This study aims to elucidate the functional capability of gut microbio...

Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method.

European journal of psychotraumatology
Approximately 70% of individuals globally experience at least one traumatic event in their lifetimes, potentially leading to posttraumatic stress disorder (PTSD). Understanding the development of PTSD and devising effective prevention and treatment ...

Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool.

Renal failure
Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, the discriminative or calibration capacity of the currently employed models are limited. We set out to...

Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms.

Annals of medicine
OBJECTIVE: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes.

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

Clinical and experimental hypertension (New York, N.Y. : 1993)
OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the devel...