Infectious Disease

A high-resolution GIS and machine learning approach for targeted disease management and localized risk assessment in an urban setup: A case study from Bhopal, Central India.

Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like temperature, demographics, and artificial changes such as roads and buildings significantly influence dengue distribution. The use of new, emerging machine-learning techniques can aid in accurately predicting these cases and developing early warning sys...

Machine Learning-Based Prediction to Support ICU Admission Decision Making among Very Old Patients with Respiratory Infections: A Proof of Concept on a Nationwide Population-Based Cohort Study.

BackgroundIntensive care unit (ICU) hospitalizations of very old patients with acute respiratory infection have risen. The decision-making process for ICU admission is multifaceted, and the prediction of long-term survival outcome is an important component. We hypothesized that data-driven algorithms could build long-term prediction by examining massive real-life data. Our objective was to assess ...

Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs.

Escherichia coli recovered from dogs with clinical conditions such as urinary tract infections are often used to assess populations for resistance to ...

AdaptFRCNet: Semi-supervised adaptation of pre-trained model with frequency and region consistency for medical image segmentation.

Recently, large pre-trained models (LPM) have achieved great success, which provides rich feature representation for downstream tasks. Pre-training an...

Trends and advances in image-based mosquito identification and classification using machine learning models: A systematic review.

Mosquito-borne diseases, such as Yellow fever, Dengue, and Zika, pose a significant global health threat, causing millions of deaths annually. Traditi...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is a leading cause of in-hospital mortality. Early de...

Single-shot, receptor-free, rapid detection and classification of five respiratory viruses by machine learning integrated SERS sensing platform.

A machine learning integrated SERS sensing platform is developed for a single-shot, receptor-free, rapid detection and classification of five respirat...

Machine learning-assisted ratiometric fluorescence sensor array for recognition of multiple quinolones antibiotics.

Developing analytical methods for simultaneous detection of multiple antibiotic residues is crucial for environmental protection and human health. In ...

Multimodal image registration for effective thermographic fever screening

Fever screening based on infrared thermographs (IRTs) is a viable mass screening approach during infectious disease pandemics, such as Ebola and SAR...

Multi-Source COVID-19 Detection via Variance Risk Extrapolation

We present our solution for the Multi-Source COVID-19 Detection Challenge, which aims to classify chest CT scans into COVID and Non-COVID categories...

An efficient plant disease detection using transfer learning approach

Plant diseases pose significant challenges to farmers and the agricultural sector at large. However, early detection of plant diseases is crucial to...

Extracting True Virus SERS Spectra and Augmenting Data for Improved Virus Classification and Quantification.

Surface-enhanced Raman spectroscopy (SERS) is a transformative tool for infectious disease diagnostics, offering rapid and sensitive species identific...

MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification

Current medical image analysis systems are typically task-specific, requiring separate models for classification and segmentation, and lack the flex...

Advances in Intelligent Hearing Aids: Deep Learning Approaches to Selective Noise Cancellation

The integration of artificial intelligence into hearing assistance marks a paradigm shift from traditional amplification-based systems to intelligen...

Disentangled representations of microscopy images

Microscopy image analysis is fundamental for different applications, from diagnosis to synthetic engineering and environmental monitoring. Modern ac...

EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis

Hepatic echinococcosis (HE) is a widespread parasitic disease in underdeveloped pastoral areas with limited medical resources. While CNN-based and T...

Bibliometric analysis of research on spinal tuberculosis in last 5 years.

BACKGROUND: Spinal tuberculosis (TB), also known as Pott's spine, remains a significant global health issue, particularly in regions with a high TB bu...

[Methodological breakthroughs and challenges in research of soil phage microecology].

Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance...

Focus on juvenile hypertension, deep learning-qualified body composition for risk stratification, infective endocarditis, and mixed valvular heart disease.

Harnessing advances in mechanisms, detection, and strategies to combat antimicrobial resistance.

Antimicrobial resistance (AMR) is a growing global health crisis, threatening the effectiveness of antibiotics and other antimicrobial agents, leading...