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Mohamad Amin Pourhoseingholi

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Medical Statistician

University of Nottingham

United Kingdom

Research Interests

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Recent Grants

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Calculating Burden of hepatitis B virus (HBV) in Iran by 2030: a modelling study

Open Date: 2019-01-01

Close Date:

Grant: Close

Estimating the incidence Rate of Esophageal Cancer among Northerners living in Tehran

Open Date: 2019-01-01

Close Date:

Grant: Close

Modeling the High Dimensional Data with Penalized Estimators and its application for proteomic changes in Helicobacter pylori

Open Date: 2019-01-01

Close Date: 2021-01-01

Grant: Close

Prognostic Value of HLA class one expression in Gastrointestinal Cancers: A Meta Analysis

Open Date: 2018-01-01

Close Date: 2019-01-01

Grant: Close

Bayesian adjustment for over-estimation and under-estimation of colorectal cancer incidence in Iranian provinces

Open Date: 2017-01-01

Close Date: 2018-01-01

Articles (20)

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2023

Collaborators (4)

Magdalena Sereda

University of Nottingham

UNITED KINGDOM

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Ali Nosrat

UNITED STATES

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Derek Hoare

Associate Professor

University of Nottingham

UNITED KINGDOM

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Marcus Kaiser

Professor at School of Psychology

University of Nottingham

UNITED KINGDOM

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Mohamad Amin Pourhoseingholi

Research Interests

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Recent Grants

Articles (20)

Validity, reliability, and readability of Artificial Intelligence chatbots as public sources of information on hearing loss: a comparative evaluation of ChatGPT, Bing, Gemini, and Perplexity

Auricular Ultrasonic Vagus Nerve Stimulation: Effectiveness of Blinding and the Occurrence of Adverse Effects in People with Tinnitus

Piperacillin-tazobactam/meropenem vs colistin/meropenem for carbapenem-resistant Klebsiella Pneumoniae-related ventilator-associated pneumonia

Auricular Ultrasonic Vagus Nerve Stimulation: Effectiveness of Blinding and Occurrence of Adverse Effects in Healthy Volunteers

Bayesian age-period-cohort projection of cancers in Iran: a modeling study

Atorvastatin Effect on COVID-19 Outcomes: A Propensity Score Matched Study on Hospitalized Patients.

Accuracy of the Discriminatory Ability of Combined Fecal Microbiota Panel in the Early Detection of Patients with Colorectal Cancer

Assemblage characterization of Giardia duodenalis in South Khorasan province, eastern Iran, using HRM real-time PCR method

Assessing the effect of remdesivir alone and in combination with corticosteroids on time to death in COVID-19: A propensity score-matched analysis

ChatGPT as an Inventor: Does It Make Sense?

Classification and Diagnostic Prediction of Colorectal Cancer Mortality Based on Machine Learning Algorithms: A Multicenter National Study

Comparative analysis of feature selection techniques for COVID-19 dataset

Comparison of the efficacy of diltiazem versus fluoxetine in the treatment of distal esophageal spasm: A randomized-controlled-trial

High prevalence of SARS-Coronavirus-2 in patients with inflammatory bowel disease and the role of soluble angiotensin converting Enzyme2

Machine learning-based classifiers to predict metastasis in colorectal cancer patients

Palliative care nurse: A quantitative study of caring for neonates at end-of-life stage

Prevalence of depressive symptoms and suicidal behaviors among Iranian high school students: A systematic review and meta-analysis

Validity and reliability of artificial intelligence chatbots as public sources of information on endodontics

A Bayesian approach to correct the under-count of cancer registry statistics before population-based cancer registry program

Author Correction: Predicting metastasis in gastric cancer patients: machine learning-based approaches (Scientific Reports, (2023), 13, 1, (4163), 10.1038/s41598-023-31272-w)

Collaborators (4)

Magdalena Sereda

Ali Nosrat

Derek Hoare

Marcus Kaiser

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