Latest AI and machine learning research in primary care for healthcare professionals.
Purpose To investigate the issues of generalizability and replication of deep learning models by assessing performance of a screening mammography deep learning system developed at New York University (NYU) on a local Australian dataset. Materials and Methods In this retrospective study, all individuals with biopsy or surgical pathology-proven lesions and age-matched controls were identified from a...
Purpose To develop an artificial intelligence (AI) deep learning tool capable of predicting future breast cancer risk from a current negative screening mammographic examination and to evaluate the model on data from the UK National Health Service Breast Screening Program. Materials and Methods The OPTIMAM Mammography Imaging Database contains screening data, including mammograms and information on...
Background Comparative performance between artificial intelligence (AI) and breast US for women with dense breasts undergoing screening mammography re...
Applications of Artificial Intelligence (AI) deep-learning models to screening for clinical conditions continue to evolve. Instances provided in this ...
This study investigates the use of ensemble learning methods for the automatic detection of chronic kidney disease (CKD) stages during sleep. We appli...
Prediabetes is a critical health condition characterized by elevated blood glucose levels that fall below the threshold for Type 2 diabetes (T2D) diag...
Rising diabetes rates have led to increased healthcare costs and health complications. An estimated half of diabetes cases remain undiagnosed. Early a...
Drawing inspiration from convolutional neural networks, graph convolutional networks (GCNs) have been implemented in various applications. Yet, the in...
The prevalence of obstructive sleep apnea comorbid with diabetes is high while the awareness of diabetes is low. There is a strong need for new diagno...
Dysarthria is a very common motor speech symptom in Parkinson's disease impairing normal communications of patients. Detection of dysarthria could ass...
Diabetic retinopathy (DR) is a serious complication of diabetes that can lead to vision impairment or even blindness if not detected and treated in th...
The importance of early Alzheimer's Disease screening is becoming more apparent, given the fact that there is no way to revert the patient's status af...
The cuffless estimation of blood pressure (BP) has become a prominent area of research in recent years fueled by its potential clinical implications a...
Understanding the complex relationships of biomarkers in diabetes is pivotal for advancing treatment strategies, a pressing need in diabetes researc...
Dementia is a mental illness that people live with all across the world. No one is immune. Nothing can predict its onset. The true story of dementia...
This work aims to develop explainable models to predict the interactions between bitter molecules and TAS2Rs via traditional machine-learning and de...
Tuberculosis persists as a global health crisis, especially in resource-limited populations and remote regions, with more than 10 million individual...
Calculating mealtime insulin doses poses a significant challenge for individuals with Type 1 Diabetes (T1D). Doses should perfectly compensate for e...
With the advancing capabilities of computational methodologies and resources, ultra-large-scale virtual screening via molecular docking has emerged ...
Early disease detection in veterinary care relies on identifying subclinical abnormalities in asymptomatic animals during wellness visits. This stud...