Prognostic models in COVID-19 infection that predict severity: a systematic review

C Buttia, E Llanaj, H Raeisi-Dehkordi, L Kastrati… - European journal of …, 2023 - Springer
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …

[HTML][HTML] Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review

C Lu, R Shiradkar, Z Liu - Chinese Journal of Cancer Research, 2021 - ncbi.nlm.nih.gov
In the last decade, the focus of computational pathology research community has shifted
from replicating the pathological examination for diagnosis done by pathologists to …

Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis

R Chen, J Chen, S Yang, S Luo, Z Xiao, L Lu… - International Journal of …, 2023 - Elsevier
Background Accurate prediction of prognostic outcomes in patients with COVID-19 could
facilitate clinical decision-making and medical resource allocation. However, little is known …

Exploring the clinical benefit of ventilation therapy across various patient groups with COVID-19 using real-world data

M Abbasi-Kangevari, A Ghanbari, MR Malekpour… - Scientific Reports, 2023 - nature.com
Scarcity of ventilators during COVID-19 pandemic has urged public health authorities to
develop prioritization recommendations and guidelines with the real-time decision-making …

Artificial intelligence-based model for COVID-19 prognosis incorporating chest radiographs and clinical data; a retrospective model development and validation study

SL Walston, T Matsumoto, Y Miki… - The British Journal of …, 2022 - academic.oup.com
Objectives: The purpose of this study was to develop an artificial intelligence-based model to
prognosticate COVID-19 patients at admission by combining clinical data and chest …

Deep-learning-based hepatic fat assessment (DeHFt) on non-contrast chest CT and its association with disease severity in COVID-19 infections: A multi-site …

G Modanwal, S Al-Kindi, J Walker, R Dhamdhere… - …, 2022 - thelancet.com
Background Hepatic steatosis (HS) identified on CT may provide an integrated
cardiometabolic and COVID-19 risk assessment. This study presents a deep-learning-based …

Deep Learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study

A Hiremath, VS Viswanathan, K Bera… - Computers in Biology …, 2024 - Elsevier
Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion.
In this study we employed machine learning and statistical atlas-based approaches to …

COVID-19 disease prediction using weighted ensemble transfer learning

P Kumar, A Singh - IJIMAI, 2023 - dialnet.unirioja.es
Health experts use advanced technological equipment to find complex diseases and
diagnose them. Medical imaging nowadays is popular for detecting abnormalities in human …

Optimization of Ventilation Therapy Prioritization Strategies among Patients with COVID-19: Lessons Learned from Real-World Data of nearly 600,000 Hospitalized …

M Abbasi-Kangevari, A Ghanbari, MR Malekpour… - medRxiv, 2022 - medrxiv.org
Objective To investigate the benefit of ventilation therapy among various patient groups with
COVID-19 admitted to hospitals, based on the real-world data of hospitalized adult patients …

A Conceptual Review on Artificial Intelligence in Biomedical Applications

I Muazu, F Al-Turjman, İ Etikan - 2022 International Conference …, 2022 - ieeexplore.ieee.org
A wide range of human efforts are being impacted by AI in our daily lives. Numerous
organizations, including the health sector, are also taking steps to adapt to AI technology …