Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.

This study aimed to develop machine learning (ML) models to predict diabetic complications in patien...

Optimal structural characteristics of osteoinductivity in bioceramics derived from a novel high-throughput screening plus machine learning approach.

Osteoinduction is an important feature of the next generation of bone repair materials. But the key ...

Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.

Diabetes is a growing global health concern, affecting millions and leading to severe complications ...

Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.

OBJECTIVE: To develop a machine learning (ML)-based admission screening model for hospital-acquired ...

Gut microbiome research: Revealing the pathological mechanisms and treatment strategies of type 2 diabetes.

The high prevalence and disability rate of type 2 diabetes (T2D) caused a huge social burden to the ...

Artificial intelligence utilization in cancer screening program across ASEAN: a scoping review.

BACKGROUND: Cancer remains a significant health challenge in the ASEAN region, highlighting the need...

Automatic development of speech-in-noise hearing tests using machine learning.

Understanding speech in noisy environments is a primary challenge for individuals with hearing loss,...

Prostate Cancer Screening Among Traditionally Underserved Populations at a Large Public Safety-Net Institution.

BACKGROUND: Existing literature underscores racial and sociodemographic disparities in prostate canc...

Machine learning for high-risk hospitalization prediction in outpatient individuals with diabetes at a tertiary hospital.

OBJECTIVE: To characterize, via a predictive model using real-world data, patients with diabetes wit...

Nasopharyngeal cancer screening and immunotherapy efficacy evaluation based on plasma separation combined with label-free SERS technology.

BACKGROUND: In recent years, significant progress has been made in the treatment of nasopharyngeal c...

Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.

BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for t...

Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predic...

Artificial intelligence in the diagnosis and management of refractive errors.

Refractive error is among the leading causes of visual impairment globally. The diagnosis and manage...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or tria...

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