AIMC Topic: Chemotherapy, Adjuvant
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Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer.
Breast cancer research and treatment
Jan 31, 2024
PURPOSE: The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL).
Fusion Radiomics-Based Prediction of Response to Neoadjuvant Chemotherapy for Osteosarcoma.
Academic radiology
Dec 27, 2023
RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is the most crucial prognostic factor for osteosarcoma (OS), it significantly prolongs progression-free survival and improves the quality of life. This study aims to develop a deep learning rad...
Humans
Retrospective Studies
Female
Young Adult
Chemotherapy, Adjuvant
Osteosarcoma
Bone Neoplasms
Predictive Value of Tests
Adolescent
Child
Nomograms
Male
Adult
Contrast Media
Middle Aged
Sensitivity and Specificity
Magnetic Resonance Imaging
Treatment Outcome
Deep Learning
Radiomics
Neoadjuvant Therapy
Biology-guided deep learning predicts prognosis and cancer immunotherapy response.
Nature communications
Aug 23, 2023
Substantial progress has been made in using deep learning for cancer detection and diagnosis in medical images. Yet, there is limited success on prediction of treatment response and outcomes, which has important implications for personalized treatmen...
Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics.
Cell reports. Medicine
Aug 8, 2023
The tumor microenvironment (TME) plays a critical role in disease progression and is a key determinant of therapeutic response in cancer patients. Here, we propose a noninvasive approach to predict the TME status from radiological images by combining...
Predictive modelling for high-risk stage II colon cancer using auto-artificial intelligence.
Techniques in coloproctology
Aug 28, 2022
BACKGROUND: Recently, stratification of high-risk stage II colon cancer (CC) and the need for adjuvant chemotherapy have been the focus of attention. The aim of this retrospective study was to define high-risk factors for recurrent stage II CC using ...
mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning.
Frontiers in immunology
Aug 23, 2022
Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer stem cells and metabolic reprogramming have an important effect on tumor progression and drug resistance, their combined effect on CRC prognosis remains...
A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.
The Lancet. Oncology
Aug 11, 2022
BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and was observed to outperform established molecular and morphological markers of patient outcome after p...
A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer.
Journal of cancer research and clinical oncology
Mar 24, 2022
PURPOSE: Most of Stage II/III colorectal cancer (CRC) patients can be cured by surgery alone, and only certain CRC patients benefit from adjuvant chemotherapy. Risk stratification based on deep-learning from haematoxylin and eosin (H&E) images has be...
Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer.
Nature communications
Feb 10, 2022
Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-base...
Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.
Scientific reports
Sep 27, 2021
High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist ...
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