AIMC Topic: Prognosis

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Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning.

Cancer letters
Immunotherapy has become a cornerstone in the treatment of advanced gastric cancer (GC). However, identifying reliable predictive biomarkers remains a considerable challenge. This study demonstrates the potential of integrating multimodal baseline da...

Multi-transcriptomics predicts clinical outcome in systemically untreated breast cancer patients with extensive follow-up.

Breast cancer research : BCR
BACKGROUND: Prognostic tools for determining patients with indolent breast cancers (BCs) are far from optimal, leading to extensive overtreatment. Several studies have demonstrated mRNAs, lncRNAs and miRNAs to have prognostic potential in BC. Because...

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.

BMC medical informatics and decision making
BACKGROUND: Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), characterized by high incidence, elevated mortality rates, and substantial therapeutic challenges. Accurate prediction of mortality in patients with hemorr...

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Scientific reports
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Scientific reports
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...

Decision level scheme for fusing multiomics and histology slide images using deep neural network for tumor prognosis prediction.

Scientific reports
Molecular biostatistical workflows in oncology often rely on predictive models that use multimodal data. Advances in deep learning and artificial intelligence technologies have enabled the multimodal fusion of large volumes of multimodal data. Here, ...

Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.

BMC cancer
BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organization (WHO) grade 4 Central Nervous System (CNS) gliomas is highly relevant for prognostic stratification and personalized treatment.

A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma.

Scientific reports
Transcription factors (TFs) are pivotal in tumor initiation and progression, regulating downstream gene expression and modulating cellular processes. In this study, we conducted a comprehensive analysis of TF gene sets to define the molecular subtype...

Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after curative-intent resection.

Scientific reports
Hilar cholangiocarcinoma (hCCA), a rare cancer of the biliary system, has a poor prognosis. This study aimed to investigate the risk factors affecting the survival of patients with hCCA after curative-intent resection and establish a survival predict...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Scientific reports
Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcomes. We performed an integrative analysis of multi-omics data from 274 CRC patients to investigate the impact of gut microbiota composition on prognosi...