STDs

Identification of key drivers of antimicrobial resistance in using machine learning.

With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML) models show promise for AMR prediction in diagnostics but require a deep understanding of internal processes to use effectively. Our study utilised A...

The Relationship Between Metal Exposure and HPV Infection: Evidence from Explainable Machine Learning Methods.

HPV is a ubiquitous pathogen implicated in cervical and other cancers. Although vaccines are available, they do not encompass all subtypes. Meanwhile, metal exposure may elevate the risk of HPV infection and amplify its carcinogenic potential, but studies to further elucidate this relationship are insufficient. This study entailed a cross-sectional analysis utilizing data from the National Health ...

Genome composition-based deep learning predicts oncogenic potential of HPVs.

Human papillomaviruses (HPVs) account for more than 30% of cancer cases, with definite identification of the oncogenic role of viral and genes. Howe...

Utilizing Deep Feature Fusion for Automatic Leukemia Classification: An Internet of Medical Things-Enabled Deep Learning Framework.

Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diag...

Development, Validation, and Implementation of an Augmented Multiwell, Multitarget Quantitative PCR for the Analysis of Human Papillomavirus Genotyping through Software Automation, Data Science, and Artificial Intelligence.

The value of human papillomavirus (HPV) testing for cervical cancer screening is well established; however, its use as a primary screening option or a...

Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.

BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage r...

Explainable prediction model for the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma using CNN on CT images.

Several studies have emphasised how positive and negative human papillomavirus (HPV+  and HPV-, respectively) oropharyngeal squamous cell carcinoma (O...

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.

Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here...

Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration.

Accurately predicting potential evapotranspiration (PET) is crucial in water resource management, agricultural planning, and climate change studies. T...

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of st...

Deep learning assisted logic gates for real-time identification of natural tetracycline antibiotics.

The overuse and misuse of tetracycline (TCs) antibiotics, including tetracycline (TTC), oxytetracycline (OTC), doxycycline (DC), and chlortetracycline...

PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction.

Biomolecular interaction recognition between ligands and proteins is an essential task, which largely enhances the safety and efficacy in drug discove...

Enhancing cervical cancer detection and robust classification through a fusion of deep learning models.

Cervical cancer, the second most prevalent cancer affecting women, arises from abnormal cell growth in the cervix, a crucial anatomical structure with...

Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant public...

Impact of F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers.

We aimed to investigate the effects of F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) a...

Fully automated 3D machine learning model for HPV status characterization in oropharyngeal squamous cell carcinomas based on CT images.

BACKGROUND: Human papillomavirus (HPV) status plays a major role in predicting oropharyngeal squamous cell carcinoma (OPSCC) survival. This study asse...

Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.

To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers...

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in ...

Fabric tearing performance state perception and classification driven by multi-source data.

The tear strength of textiles is a crucial characteristic of product quality. However, during the laboratory testing of this indicator, factors such a...

Assessing portfolio diversification via two-sample graph kernel inference. A case study on the influence of ESG screening.

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rule...