Primary Care

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Development and validation of machine learning models for MASLD: based on multiple potential screening indicators.

BACKGROUND: Multifaceted factors play a crucial role in the prevention and treatment of metabolic dy...

General structure-activity relationship models for the inhibitors of Adenosine receptors: A machine learning approach.

Adenosine receptors (A, A, A, A) play critical roles in cellular signaling and are implicated in var...

Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data.

Doxorubicin (DOXO) is a primary treatment for breast cancer but can cause cardiotoxicity in over 25%...

Predictors of glycaemic improvement in children and young adults with type 1 diabetes and very elevated HbA1c using the MiniMed 780G system.

AIMS: This study aimed to identify key factors with the greatest influence on glycaemic outcomes in ...

Opportunistic AI for enhanced cardiovascular disease risk stratification using abdominal CT scans.

This study introduces the Deep Learning-based Cardiovascular Disease Incident (DL-CVDi) score, a nov...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects...

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions.

BACKGROUND: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, charac...

Cell clone selection-impact of operation modes and medium exchange strategies on clone ranking.

Bioprocessing has been transitioning from batch to continuous processes. As a result, a considerable...

Role of Artificial Intelligence in the Detection and Management of Premalignant and Malignant Lesions of the Esophagus and Stomach.

The advent of artificial intelligence (AI) and deep learning algorithms, particularly convolutional ...

Task-oriented robotic rehabilitation for back mobility and functioning in a post-intensive care unit obese patient: A case report.

BackgroundIntensive care unit (ICU) acquired weakness is a detrimental condition characterized by mu...

Machine learning analysis of emerging risk factors for early-onset hypertension in the Tlalpan 2020 cohort.

INTRODUCTION: Hypertension is a significant public health concern. Several relevant risk factors hav...

A Paradigm of Computer Vision and Deep Learning Empowers the Strain Screening and Bioprocess Detection.

High-performance strain and corresponding fermentation process are essential for achieving efficient...

Can ChatGPT 4.0 Diagnose Acute Aortic Dissection? Integrating Artificial Intelligence into Medical Diagnostics.

Acute aortic dissection (AD) is a critical condition characterized by high mortality and frequent mi...

Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach.

BACKGROUND: Breast cancer screening plays a pivotal role in early detection and subsequent effective...

Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data.

Diagnosing Alzheimer's disease (AD) through pathological markers is typically costly and invasive. T...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

This study sought to establish and validate an interpretable CT radiomics-based machine learning mod...

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and ...

Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning.

To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease i...

Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning.

Nailfold Capillaroscopy (NFC) is a simple, non-invasive diagnostic tool used to detect microvascular...

Detecting anomalies in smart wearables for hypertension: a deep learning mechanism.

INTRODUCTION: The growing demand for real-time, affordable, and accessible healthcare has underscore...

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