Latest AI and machine learning research in infectious disease for healthcare professionals.
The coronavirus disease 2019 (COVID-19) pandemic necessitated a shift in healthcare delivery, emphasizing the need for remote patient monitoring (RPM) to minimize infection risks. This review aimed to evaluate the applications of artificial intelligence (AI) in RPM for cancer patients, exploring its impact on patient outcomes and implications for future healthcare practices. A qualitative systemat...
The emergence of drug-resistant bacteria, often referred to as "superbugs," poses a profound and escalating challenge to global health systems, surpassing the capabilities of traditional antibiotic discovery methods. As resistance mechanisms evolve rapidly, the need for innovative solutions has never been more critical. This review delves into the transformative role of AI-driven methodologies in ...
Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Although direct-acting antivirals achieve over 90% s...
Mobile devices have become essential for capturing human activity, and eXtended Data Records (XDRs) offer rich opportunities for detailed user behav...
Recent advances in deep learning have shown that learning robust feature representations is critical for the success of many computer vision tasks, ...
Active movement is essential for the survival of microorganisms like bacteria, algae and unicellular parasites. In three dimensions, both swimming a...
Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanism still unclear. DNA damage repair (DDR) is essent...
Antimicrobial-resistant (AMR) microbes are a growing challenge in healthcare, rendering modern medicines ineffective. AMR arises from antibiotic pro...
For rapidly spreading diseases where many cases show no symptoms, swift and effective contact tracing is essential. While exposure notification appl...
Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applica...
Early detection of COVID-19 is crucial for effective treatment and controlling its spread. This study proposes a novel hybrid deep learning model fo...
Background: Phage therapy shows promise for treating antibiotic-resistant Klebsiella infections. Identifying phage depolymerases that target Klebsie...
Pneumonia is a leading cause of illness and death in children, underscoring the need for early and accurate detection. In this study, we propose a n...
Individuals who are differently-able in vision cannot proceed with their day-to-day activities as smoothly as other people do. Especially independen...
Chest X-rays play a pivotal role in diagnosing respiratory diseases such as pneumonia, tuberculosis, and COVID-19, which are prevalent and present u...
Lightweight deep learning approaches for malaria detection have gained attention for their potential to enhance diagnostics in resource constrained ...
Appropriate identification of burn depth and size is paramount. Despite the development of burn depth assessment aids [eg, laser Doppler imaging (LDI)...
Epidemiological models can aid policymakers in reducing disease spread by predicting outcomes based on disease dynamics and contact network characte...
To restore proper blood flow in blocked coronary arteries via angioplasty procedure, accurate placement of devices such as catheters, balloons, and ...
The increasing demand for larger and higher fidelity simulations has made Adaptive Mesh Refinement (AMR) and unstructured mesh techniques essential ...