Infectious Disease

"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health self-education. This study examined simulations with ChatGPT for its use in public education of sexual health of Black women, specifically in HIV prevention and/or HIV PrEP use. The research questions guiding the study are as follows: (a) does the i...

Emergence of accurate atomic energies from machine-learned noble-gas potentials.

The quantum theory of atoms in molecules gives access to well-defined local atomic energies. Due to their locality, these energies are potentially interesting in fitting atomistic machine learning models as they inform about physically relevant properties. However, computationally, quantum-mechanically accurate local energies are notoriously difficult to obtain for large systems. Here, we show tha...

Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images

The rising incidence of skin cancer, coupled with limited public awareness and a shortfall in clinical expertise, underscores an urgent need for adv...

Unsupervised Out-of-Distribution Detection in Medical Imaging Using Multi-Exit Class Activation Maps and Feature Masking

Out-of-distribution (OOD) detection is essential for ensuring the reliability of deep learning models in medical imaging applications. This work is ...

Thermal Detection of People with Mobility Restrictions for Barrier Reduction at Traffic Lights Controlled Intersections

Rapid advances in deep learning for computer vision have driven the adoption of RGB camera-based adaptive traffic light systems to improve traffic s...

SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning.

To develop scanning electron microscopy-based Trainable Weka (Waikato Environment for Knowledge Analysis) Intelligent Segmentation Technology (SEMTWI...

Severe community-acquired pneumonia (sCAP): advances in management and future directions.

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity and mortality, especially among patients requiring ...

Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.

Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, inclu...

Author Correction: Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida.

Innovative fast and low-cost method for the detection of living bacteria based on trajectory.

Detection of pathogens is a major concern in many fields like medicine, pharmaceuticals, or agri-food. Most conventional detection methods require ski...

The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis.

BACKGROUND: The Surviving Sepsis Campaign strongly recommends that all hospitals screen for sepsis as part of performance improvement. The effect of s...

Indirect Detection of Swine Influenza Activity in Porcine Blood Using Raman Spectroscopy and Machine Learning.

Over the past decade, several swine influenza variants, including H1N1 and H1N2, have been periodically detected in swine. Raman spectroscopy (RS) off...

Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review.

COVID-19 was one of the most serious global public health emergencies in recent years, and its extremely fast spreading speed had a profound negative ...

An Innovative Deep Learning Approach for Ventilator-Associated Pneumonia (VAP) Prediction in Intensive Care Units-Pneumonia Risk Evaluation and Diagnostic Intelligence via Computational Technology (PREDICT).

Ventilator-associated pneumonia (VAP) is a common and serious ICU complication, affecting up to 40% of mechanically ventilated patients. The diagnosi...

Machine Learning-Driven Consensus Modeling for Activity Ranking and Chemical Landscape Analysis of HIV-1 Inhibitors.

This study aimed to develop a predictive model to classify and rank highly active compounds that inhibit HIV-1 integrase (IN). : A total of 2271 pote...

Personalized Nutrition Strategies for Patients in the Intensive Care Unit: A Narrative Review on the Future of Critical Care Nutrition.

Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can result in muscle atrophy, polyneuropathy, increase...

Blockchain enabled collective and combined deep learning framework for COVID19 diagnosis.

The rapid spread of SARS-CoV-2 has highlighted the need for intelligent methodologies in COVID-19 diagnosis. Clinicians face significant challenges du...

Dual level dengue diagnosis using lightweight multilayer perceptron with XAI in fog computing environment and rule based inference.

Over the last fifty years, arboviral infections have made an unparalleled contribution to worldwide disability and morbidity. Globalization, populatio...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) cou...

Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning.

BACKGROUND: Pneumonia is a major threat to the health of children, especially those under the age of five. Mycoplasma  pneumoniae infection is a core ...