Infectious Disease

Too Many Definitions of Sepsis: Can Machine Learning Leverage the Electronic Health Record to Increase Accuracy and Bring Consensus?

A Bayesian classification model for discriminating common infectious diseases in Zhejiang province, China.

To develop a classification model for accurately discriminating common infectious diseases in Zhejiang province, China.Symptoms and signs, abnormal lab test results, epidemiological features, as well as the incidence rates were treated as predictors, and were collected from the published literature and a national surveillance system of infectious disease. A classification model was established usi...

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks.

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines a...

Can machine learning optimize the efficiency of the operating room in the era of COVID-19?

The cancellation of large numbers of surgical procedures because of the coronavirus disease 2019 (COVID-19) pandemic has drastically extended wait lis...

Postimplementation Evaluation of a Machine Learning-Based Deterioration Risk Alert to Enhance Sepsis Outcome Improvements.

Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accurately than point-score tools. In patients with sepsis,...

AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images.

Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantita...

Hybrid Design of Isonicotinic Acid Hydrazide Derivatives: Machine Learning Studies, Synthesis and Biological Evaluation of their Antituberculosis Activity.

BACKGROUND: Tuberculosis (TB) is an infection disease caused by Mycobacterium tuberculosis (Mtb) bacteria. One of the main causes of mortality from TB...

iATP: A Sequence Based Method for Identifying Anti-tubercular Peptides.

BACKGROUND: Tuberculosis is one of the biggest threats to human health. Recent studies have demonstrated that anti-tubercular peptides are promising c...

Knowledge Discovery With Machine Learning for Hospital-Acquired Catheter-Associated Urinary Tract Infections.

Massive generation of health-related data has been key in enabling the big data science initiative to gain new insights in healthcare. Nursing can ben...

Recent Advancement in Predicting Subcellular Localization of Mycobacterial Protein with Machine Learning Methods.

Mycobacterium tuberculosis (MTB) can cause the terrible tuberculosis (TB), which is reported as one of the most dreadful epidemics. Although many bioc...

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation in Digital Pathology.

The diagnosis of disease often requires analysis of a biopsy. Many diagnoses depend not only on the presence of certain features but on their location...

Studies for Bacterystic Evaluation against of 2-Naphthoic Acid Analogues.

BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, ...

Deep Learning in Medical Image Analysis.

Deep learning is the state-of-the-art machine learning approach. The success of deep learning in many pattern recognition applications has brought exc...

The Genome3D Consortium for Structural Annotations of Selected Model Organisms.

Genome3D consortium is a collaborative project involving protein structure prediction and annotation resources developed by six world-leading structur...

The most cited and co-cited COVID-19 articles: Knowledge base for rehabilitation team members.

BACKGROUND: The COVID-19 outbreak pandemic is a situation without a tested action plan. Rehabilitation team members have been called for duty with new...

Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.

OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in ...

Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are...

Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical ...

Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review.

BACKGROUND: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to de...

Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases.

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population ...