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Hepatitis C

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Association of Individual and Community Factors With Hepatitis C Infections Among Pregnant People and Newborns.

JAMA health forum
IMPORTANCE: The opioid crisis has increasingly affected pregnant people and infants. Hepatitis C virus (HCV) infections, a known complication of opioid use, grew in parallel with opioid-related complications; however, the literature informing individ...

Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease.

Frontiers in public health
Machine learning algorithms are excellent techniques to develop prediction models to enhance response and efficiency in the health sector. It is the greatest approach to avoid the spread of hepatitis C, especially injecting drugs, is to avoid these b...

HBCVTr: an end-to-end transformer with a deep neural network hybrid model for anti-HBV and HCV activity predictor from SMILES.

Scientific reports
Hepatitis B and C viruses (HBV and HCV) are significant causes of chronic liver diseases, with approximately 350 million infections globally. To accelerate the finding of effective treatment options, we introduce HBCVTr, a novel ligand-based drug des...

Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C prediction.

Scientific reports
Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply de...

A potential new way to facilitate HCV elimination: The prediction of viremia in anti-HCV seropositive patients using machine learning algorithms.

Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology
BACKGROUND AND STUDY AIMS: The present study was undertaken to design a new machine learning (ML) model that can predict the presence of viremia in hepatitis C virus (HCV) antibody (anti-HCV) seropositive cases.

Near infrared spectroscopy (NIRS) and machine learning as a promising tandem for fast viral detection in serum microsamples: A preclinical proof of concept.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Fast detection of viral infections is a key factor in the strategy for the prevention of epidemics expansion and follow-up. Hepatitis C is paradigmatic within viral infectious diseases and major challenges to elimination still remain. Near infrared s...

A predictive study on HCV using automated machine learning models.

Computers in biology and medicine
Hepatitis C virus (HCV) infection represents a significant contributor to chronic liver disease on a global scale. The prompt identification and management of HCV are imperative in order to avert complications and to maintain control over the disease...

Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.

Journal of medical virology
Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Although direct-acting antivirals achieve over 90% success rate, treatment failures still occur, particularly when pan-genotypic DAAs are unavailable, a...

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Science advances
Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C (HCV) causing approximately 1 million deaths annually, primarily due to liver cancer and cirrhosis. More than 1.5 million people contract HCV each yea...

Treatment of Porphyria Cutanea Tarda Scarring With Combination Laser Treatment and a Pilot Use of Artificial Intelligence to Quantify Laser Results.

Journal of cosmetic dermatology
BACKGROUND: Porphyria cutanea tarda (PCT) is the most common subtype of porphyria and results from a deficiency of the enzyme uroporphyrinogen decarboxylase. Even after successful treatment, patients can be left with significant scarring, and there i...