AI Medical Compendium Journal:
Hypertension research : official journal of the Japanese Society of Hypertension

Showing 1 to 8 of 8 articles

Visit-to-visit blood pressure variability and clinical outcomes in peritoneal dialysis - based on machine learning algorithms.

Hypertension research : official journal of the Japanese Society of Hypertension
This study aims to investigate the association between visit-to-visit blood pressure variability (VVV) in early stage of continuous ambulatory peritoneal dialysis (CAPD) and long-term clinical outcomes, utilizing machine learning algorithms. Patients...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Hypertension research : official journal of the Japanese Society of Hypertension
Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound is a typical way to diagnose hypertension-mediated heart change, it often fails to detect early subtle structural changes. Electrocardiogram(ECG) repre...

Does clinical practice supported by artificial intelligence improve hypertension care management? A pilot systematic review.

Hypertension research : official journal of the Japanese Society of Hypertension
Although artificial intelligence (AI) is considered to be a promising tool, evidence for the effectiveness of AI-supported clinical practice for lowering blood pressure (BP) in the real world is scarce. We conducted a systematic review to elucidate w...

Recent developments in machine learning modeling methods for hypertension treatment.

Hypertension research : official journal of the Japanese Society of Hypertension
Hypertension is the leading cause of cardiovascular complications. This review focuses on the advancements in medical artificial intelligence (AI) models aimed at individualized treatment for hypertension, with particular emphasis on the approach to ...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

Hypertension research : official journal of the Japanese Society of Hypertension
In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (...

Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Hypertension research : official journal of the Japanese Society of Hypertension
Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extensively in the medical field but rarely in the mining of genetic information. This study aims to deter...

Future possibilities for artificial intelligence in the practical management of hypertension.

Hypertension research : official journal of the Japanese Society of Hypertension
The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming increasingly more common. This review describes the current status and a future possibility for art...