Hepatitis

Mutation prediction in the SARS-CoV-2 genome using attention-based neural machine translation.

Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has been evolving rapidly after causing havoc worldwide in 2020. Since then, it has been very hard to contain the virus owing to its frequently mutating nature. Changes in its genome lead to viral evolution, rendering it more resistant to existing vaccines and drugs. Predicting viral mutations beforehand will help in gearing up against m...

DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm.

MOTIVATION: Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as potential candidates in the pursuit of novel antiviral drugs. These peptides show vigorous antiviral activity against a diverse range of viruses by targeting different phases of the viral life cycle. Therefore, the accu...

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavourable, primarily attributable to the high incidenc...

Analysis of Emerging Variants of Turkey Reovirus using Machine Learning.

Avian reoviruses continue to cause disease in turkeys with varied pathogenicity and tissue tropism. Turkey enteric reovirus has been identified as a c...

A nomogram for predicting prognosis in patients with transjugular intrahepatic portosystemic shunt creation based on deep learning-derived spleen volume-to-platelet ratio.

OBJECTIVES: The objective of our study was to develop a nomogram to predict post-transjugular intrahepatic portosystemic shunt (TIPS) survival in pati...

Artificial Intelligence Approach for Severe Dengue Early Warning System.

Dengue fever is a viral infectious disease transmitted through mosquito bites, and has symptoms ranging from mild flu-like symptoms to deadly complica...

[Evaluation of brain age changes in patients with liver cirrhosis and hepatic encephalopathy with deep learning models based on structural magnetic resonance imaging].

To investigate the brain aging in patients with cirrhosis and hepatic encephalopathy(HE), constructed a prediction model of brain age based on deep l...

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips.

Health-related social media data generated by patients and the public provide valuable insights into patient experiences and opinions toward health is...

Forecasting deep learning-based risk assessment of vector-borne diseases using hybrid methodology.

BACKGROUND: Dengue fever is rapidly becoming Malaysia's most pressing health concern, as the reported cases have nearly doubled over the past decade. ...

Identification and Prioritization of Health Indexes in Nomadic Tribespeople by Fuzzy Delphi Method: An Ecological Study.

The migratory lifestyle of nomadic communities, combined with the lack of a suitable health-related organizational structure, has made it difficult to...

[A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B].

To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to...

[Experimental study of APB-DOCK8 transgenic tomato vaccine for caries prevention].

PURPOSE: To observe the anti-caries effect of transgenic tomato anti-caries vaccine after immunization with SD rats by gavage and to explore its immun...

Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites.

The coronavirus disease 2019 (COVID-19) pandemic has spurred a wide range of approaches to control and combat the disease. However, selecting an effec...

Deep learning to predict esophageal variceal bleeding based on endoscopic images.

OBJECTIVE: Esophageal varix (EV) bleeding is a particularly serious complications of cirrhosis. Prediction of EV bleeding requires extensive endoscopy...

Humoral Response After Two Doses of COVISHIELD Vaccine in Patients Undergoing Maintenance Hemodialysis.

OBJECTIVES: Maintenance hemodialysis (MHD) patients are at increased risk of contracting coronavirus disease 2019 (COVID-19). Vaccine against COVID-19...

SEINN: A deep learning algorithm for the stochastic epidemic model.

Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appro...

Reinforcement learning relieves the vaccination dilemma.

The main goal of this paper is to study how a decision-making rule for vaccination can affect epidemic spreading by exploiting the Bush-Mosteller (BM)...

[Network meta-analysis comparing the clinical outcomes and safety of robotic, laparoscopic, and transanal total rectal mesenteric resection for rectal cancer].

To methodically assess the clinical effectiveness and safety of robot-assisted total rectal mesenteric resection (RTME), laparoscopic-assisted total ...

COPPER: an ensemble deep-learning approach for identifying exclusive virus-derived small interfering RNAs in plants.

Antiviral defenses are one of the significant roles of RNA interference (RNAi) in plants. It has been reported that the host RNAi mechanism machinery ...

Development and validation of a deep learning model to diagnose COVID-19 using time-series heart rate values before the onset of symptoms.

One of the effective ways to minimize the spread of COVID-19 infection is to diagnose it as early as possible before the onset of symptoms. In additio...