Military Medicine

A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms.

Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not universal availability of qualified personnel, e.g. in developing countries, many efforts are made worldwide to propose computational tools for detecting a...

Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.

Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients' satisfaction relating to telemedicine adoption in rural public hospitals settings in Bangladesh through the adaptation of Expectation Disconfirmation Theory extended by Social Cognitive Theory. This research ...

Predicting outcome of daycare cognitive behavioural therapy in a naturalistic sample of patients with PTSD: a machine learning approach.

BACKGROUND: Identifying predictors for treatment outcome in patients with posttraumatic stress disorder (PTSD) is important in order to provide an eff...

Non-melanoma skin cancer diagnosis: a comparison between dermoscopic and smartphone images by unified visual and sonification deep learning algorithms.

PURPOSE: Non-melanoma skin cancer (NMSC) is the most frequent keratinocyte-origin skin tumor. It is confirmed that dermoscopy of NMSC confers a diagno...

A Novel Automate Python Edge-to-Edge: From Automated Generation on Cloud to User Application Deployment on Edge of Deep Neural Networks for Low Power IoT Systems FPGA-Based Acceleration.

Deep Neural Networks (DNNs) deployment for IoT Edge applications requires strong skills in hardware and software. In this paper, a novel design framew...

Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection.

Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is th...

Predicting Antimalarial Activity in Natural Products Using Pretrained Bidirectional Encoder Representations from Transformers.

Malaria is a threatening disease that has claimed many lives and has a high prevalence rate annually. Through the past decade, there have been many st...

Robotics for neuroendovascular intervention: Background and primer.

The simultaneous growth of robotic-assisted surgery and telemedicine in recent years has only been accelerated by the recent coronavirus disease 2019 ...

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic ...

Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer.

Machine learning (ML) holds great promise for impacting healthcare delivery; however, to date most methods are tested in 'simulated' environments that...

Methodology for comprehensive cell-level analysis of wound healing experiments using deep learning in MATLAB.

BACKGROUND: Endothelial healing after deployment of cardiovascular devices is particularly important in the context of clinical outcome. It is therefo...

Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19.

Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with mini...

Improvements to PTSD quality metrics with natural language processing.

RATIONALE AIMS AND OBJECTIVES: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) d...

Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma.

Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is...

Toward an Automatic Quality Assessment of Voice-Based Telemedicine Consultations: A Deep Learning Approach.

Maintaining a high quality of conversation between doctors and patients is essential in telehealth services, where efficient and competent communicati...

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and inte...

COVID-19 in early 2021: current status and looking forward.

Since the first description of a coronavirus-related pneumonia outbreak in December 2019, the virus SARS-CoV-2 that causes the infection/disease (COVI...

Key factors in a rigorous longitudinal image-based assessment of retinopathy of prematurity.

To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailments such as Parkinson's disease, Traumatic Brain ...

Application of Deep Learning for Diagnosing, Classifying, and Treating Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) affects nearly 200 million people and is the third leading cause of irreversible vision loss worldwide. Deep le...