Hepatitis

Prognostic Value of the Brixia Radiological Score in COVID-19 Patients: A Retrospective Study from Romania.

The novel coronavirus pandemic, SARS-CoV-2, has a variable clinical spectrum, ranging from asymptomatic to critical forms. High mortality and morbidity rates have been associated with risk factors such as comorbidities, age, sex, and virulence factors specific to viral variants. Material and Methods: We retrospectively evaluated imaging characteristics using the Brixia radiological score in relati...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration patterns and food availability enhances the virus's adaptability, in turn increasing the potential for transmission and outbreak risk. NiV infection has...

Integrating different approaches for the identification of new disruptors of HIV-1 capsid multimerization.

Human Immunodeficiency Virus (HIV) belongs to the Lentivirus genus, Retroviridae family, enveloped by a lipid bilayer within which the capsid protein ...

Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant development.

Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, c...

Discovery of SARS-CoV-2 Nsp14-Methyltransferase (MTase) Inhibitors by Harnessing Scaffold-Centric Exploration of the Ultra Large Chemical Space.

The global impact of SARS-CoV-2 underscores the need for antiviral treatments beyond vaccines. This study targets Nsp14-MTase, a viral protein essenti...

ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis

Synthesizing medical images remains challenging due to limited annotated pathological data, modality domain gaps, and the complexity of representing...

Machine learning assisted in Silico discovery and optimization of small molecule inhibitors targeting the Nipah virus glycoprotein.

The Nipah virus (NiV), a lethal pathogen from the Paramyxoviridae family, presents a significant global health threat as a result of its high mortalit...

Illuminating the black box: Machine learning enhances preoperative prediction in intrahepatic cholangiocarcinoma.

The study by Huang , published in the , advances intrahepatic cholangiocarcinoma (ICC) management by developing a machine-learning model to predict te...

Illuminating the black box: Machine learning enhances preoperative prediction in intrahepatic cholangiocarcinoma.

The study by Huang , published in the , advances intrahepatic cholangiocarcinoma (ICC) management by developing a machine-learning model to predict te...

The Association Between Hepatocellular Carcinoma and Gastrointestinal Adenocarcinoma: Is This a New Syndrome in Patients With Cirrhosis? A Case Series.

AIM: This case series aimed to explore the occurrence of synchronous hepatocellular carcinoma (HCC) and gastrointestinal adenocarcinoma in cirrhotic p...

Identification of Different Steaming Degrees of Panax quinquefolius L. Based on GC-IMS Combined With Machine Learning.

RATIONALE: Panax quinquefolius L. (PQ), a commonly used traditional Chinese medicine and a food, is usually processed into various products, including...

Hybrid Approach Combining Ultrasound and Blood Test Analysis with a Voting Classifier for Accurate Liver Fibrosis and Cirrhosis Assessment

Liver cirrhosis is an insidious condition involving the substitution of normal liver tissue with fibrous scar tissue and causing major health compli...

Machine learning algorithms reveal gut microbiota signatures associated with chronic hepatitis B-related hepatic fibrosis.

BACKGROUND: Hepatic fibrosis (HF) represents a pivotal stage in the progression and potential reversal of cirrhosis, underscoring the importance of ea...

DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution

Recent advances in diffusion models have improved Real-World Image Super-Resolution (Real-ISR), but existing methods lack human feedback integration...

SUDO: Enhancing Text-to-Image Diffusion Models with Self-Supervised Direct Preference Optimization

Previous text-to-image diffusion models typically employ supervised fine-tuning (SFT) to enhance pre-trained base models. However, this approach pri...

Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI

The segmentation of multiple organs in multi-parametric MRI studies is critical for many applications in radiology, such as correlating imaging biom...

Noninvasive prediction of esophagogastric varices in hepatitis B: An extreme gradient boosting model based on ultrasound and serology.

BACKGROUND: Severe esophagogastric varices (EGVs) significantly affect prognosis of patients with hepatitis B because of the risk of life-threatening ...

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models

Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, is a critical task with applications in pharmacovig...

De Novo Molecular Design Enabled by Direct Preference Optimization and Curriculum Learning

De novo molecular design has extensive applications in drug discovery and materials science. The vast chemical space renders direct molecular search...

A Scalable Predictive Modelling Approach to Identifying Duplicate Adverse Event Reports for Drugs and Vaccines

The practice of pharmacovigilance relies on large databases of individual case safety reports to detect and evaluate potential new causal associatio...