[HTML][HTML] All you need is data preparation: A systematic review of image harmonization techniques in Multi-center/device studies for medical support systems
Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …
centric and multi-device studies can provide more robust insights and research findings …
Predicting Immunotherapy Outcomes in Glioblastoma Patients through Machine Learning
G Mestrallet - Cancers, 2024 - mdpi.com
Simple Summary This scientific study focuses on glioblastoma, a highly aggressive cancer
with a poor prognosis. Despite various treatment modalities, including immune checkpoint …
with a poor prognosis. Despite various treatment modalities, including immune checkpoint …
Machine learning‐based CT radiomics enhances bladder cancer staging predictions: A comparative study of clinical, radiomics, and combined models
S Xiong, Z Fu, Z Deng, S Li, X Zhan, F Zheng… - Medical …, 2024 - Wiley Online Library
Background Predicting the accurate preoperative staging of bladder cancer (BLCA), which
markedly affects treatment decisions and patient outcomes, using traditional clinical …
markedly affects treatment decisions and patient outcomes, using traditional clinical …
[HTML][HTML] Predicting Resistance to Immunotherapy in Melanoma, Glioblastoma, Renal, Stomach and Bladder Cancers by Machine Learning on Immune Profiles
G Mestrallet - Onco, 2024 - mdpi.com
Simple Summary This study addresses the limitations of immune checkpoint inhibitors
(ICBs) in cancer therapy, where over 38% of patients show resistance and disease …
(ICBs) in cancer therapy, where over 38% of patients show resistance and disease …
Exploring machine learning tools in a retrospective case-study of patients with metastatic Non-Small cell lung cancer treated with first-line immunotherapy: A feasibility …
FR Ogliari, A Traverso, S Barbieri, M Montagna… - Lung Cancer, 2024 - Elsevier
Background Artificial intelligence (AI) models are emerging as promising tools to identify
predictive features among data coming from health records. Their application in clinical …
predictive features among data coming from health records. Their application in clinical …
Prediction of Glioma Resistance to Immune Checkpoint Inhibitors Based on Mutation Profile
G Mestrallet - Neuroglia, 2024 - mdpi.com
Glioma, a highly aggressive cancer, presents a daunting prognosis, with only 5% of
glioblastoma patients surviving beyond five years post diagnosis. Current therapeutic …
glioblastoma patients surviving beyond five years post diagnosis. Current therapeutic …
[HTML][HTML] Leveraging Tumor Mutation Profiles to Forecast Immune Checkpoint Blockade Resistance in Melanoma, Lung, Head and Neck, Bladder and Renal Cancers
G Mestrallet - Onco, 2024 - mdpi.com
Immune checkpoint blockade (ICB), radiotherapy, chemotherapy and surgery are currently
used as therapeutic strategies against melanoma, lung, bladder and renal cancers, but their …
used as therapeutic strategies against melanoma, lung, bladder and renal cancers, but their …
Feature Tokenizer-Transformers with Self-Training for The Prediction of PD-L1 Expression of Non-Small Cell Lung Cancer from CT
R Saber, M Tonneau, S Bahig, J Malo… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Patients with advanced non-small cell lung cancer (NSCLC) have notoriously unfavorable
clinical outcomes. Immune checkpoint inhibitors (ICIs) have recently shown promising …
clinical outcomes. Immune checkpoint inhibitors (ICIs) have recently shown promising …