AIMC Topic: Antineoplastic Combined Chemotherapy Protocols
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Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Feb 5, 2024
PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients ...
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).
Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning.
Diagnostic pathology
Jan 19, 2024
BACKGROUND: c-MYC and BCL2 positivity are important prognostic factors for diffuse large B-cell lymphoma. However, manual quantification is subject to significant intra- and inter-observer variability. We developed an automated method for quantificat...
An interpretable artificial intelligence framework for designing synthetic lethality-based anti-cancer combination therapies.
Journal of advanced research
Dec 2, 2023
INTRODUCTION: Synthetic lethality (SL) provides an opportunity to leverage different genetic interactions when designing synergistic combination therapies. To further explore SL-based combination therapies for cancer treatment, it is important to ide...
SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data.
Computer methods and programs in biomedicine
Dec 2, 2023
BACKGROUND: In Diffuse Large B-Cell Lymphoma (DLBCL), several methodologies are emerging to derive novel biomarkers to be incorporated in the risk assessment. We realized a pipeline that relies on autoencoders (AE) and Explainable Artificial Intellig...
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.
Breast cancer research : BCR
Nov 13, 2023
BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict t...
A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.
La Radiologia medica
Oct 6, 2023
BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patie...
Dose reduction and toxicity of lenalidomide-dexamethasone in multiple myeloma: A machine-learning prediction model.
Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
Sep 6, 2023
PURPOSE: Lenalidomide remains an effective drug for multiple myeloma, but it is often associated with adverse events and requires dose adjustments. The objective of this study was to propose a model for predicting whether a patient would require dose...
Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study.
Breast (Edinburgh, Scotland)
Oct 19, 2022
INTRODUCTION: Predicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic informatio...
Noncirrhotic Portal Hypertension after Trastuzumab Emtansine in HER2-positive Breast Cancer as Determined by Deep Learning-measured Spleen Volume at CT.
Radiology
Aug 9, 2022
Background Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate approved for use in human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Case reports have suggested an association between T-DM1 and portal hypertension. Purpo...
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