Primary Care

Dietary patterns associated with the incidence of hypertension among adult Japanese males: application of machine learning to a cohort study.

PURPOSE: The previous studies that examined the effectiveness of unsupervised machine learning methods versus traditional methods in assessing dietary patterns and their association with incident hypertension showed contradictory results. Consequently, our aim is to explore the correlation between the incidence of hypertension and overall dietary patterns that were extracted using unsupervised mac...

Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.

During an artificial intelligence (AI)-assisted diabetic retinopathy screening event, we performed a survey on patients´ perceptions on AI. Respondents were individuals with diabetes, mostly followed in primary healthcare with a low education level. While 49.6% of participants said they knew what AI was, only 14% reported good or expert knowledge of AI. The vast majority reported positive feelings...

Diabetic Foot Screening Guidelines and the Role of Artificial Intelligence: Time to Turn the Tide!

Despite medical and technological advancements, foot amputations continue to rise. Thus, the effort of diabetic foot management should be toward preve...

Kinome-Wide Virtual Screening by Multi-Task Deep Learning.

Deep learning is a machine learning technique to model high-level abstractions in data by utilizing a graph composed of multiple processing layers tha...

Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.

OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with an...

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of against diabetic nephropathy.

Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). has been widely used t...

The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.

Real-world registries have been critical to building the scientific knowledge of rare diseases, including Pulmonary Arterial Hypertension (PAH). In th...

Pediatric diabetes prediction using deep learning.

This study proposed a novel technique for early diabetes prediction with high accuracy. Recently, Deep Learning (DL) has been proven to be expeditious...

Dual view deep learning for enhanced breast cancer screening using mammography.

Breast cancer has the highest incidence rate among women in Ethiopia compared to other types of cancer. Unfortunately, many cases are detected at a st...

Improved Glycemic Control through Robot-Assisted Remote Interview for Outpatients with Type 2 Diabetes: A Pilot Study.

: Our research group developed a robot-assisted diabetes self-management monitoring system to support Certified Diabetes Care and Education Specialist...

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare provi...

Multicancer screening test based on the detection of circulating non haematological proliferating atypical cells.

BACKGROUND: the problem in early diagnosis of sporadic cancer is understanding the individual's risk to develop disease. In response to this need, glo...

Deep learning predicts prevalent and incident Parkinson's disease from UK Biobank fundus imaging.

Parkinson's disease is the world's fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson's disease and automate dia...

Accuracy of Online Artificial Intelligence Models in Primary Care Settings.

INTRODUCTION: The importance of preventive medicine and primary care in the sphere of public health is expanding, yet a gap exists in the utilization ...

Study of Serum Fibroblast Growth Factor 23 as a Predictor of Endothelial Dysfunction among Egyptian Patients with Diabetic Kidney Disease.

Endothelial dysfunction in patients with diabetic nephropathy is caused by nontraditional factors in addition to common risk factors (e.g., hypertensi...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strateg...

What is meant by 'integrated personalized diabetes management': A view into the future and what success should look like.

Integrated personalized diabetes management (IPDM) has emerged as a promising approach to improving outcomes in patients with diabetes mellitus (DM). ...

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new...

Application of Machine Learning Techniques to Assess Alpha-Fetoprotein at Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated with high mortality rates. Approximately 80% of cases occur in...

Oral_voting_transfer: classification of oral microorganisms' function proteins with voting transfer model.

INTRODUCTION: The oral microbial group typically represents the human body's highly complex microbial group ecosystem. Oral microorganisms take part i...