AIMC Topic: Prognosis

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Hospital Outcome of Host Heterogeneity, Organ dysfunction and Trajectory in sepsis (HOHHOT): A cohort study in the critical care unit.

BMJ open
INTRODUCTION: Prognosis estimation is the basis for establishing the personal interventions in sepsis patients. Serum biomarkers are potential tools for predicting the outcomes of sepsis patients admitted to the intensive care unit (ICU). Here, we pl...

Gut microbiota predictive of the efficacy of consolidation immunotherapy and chemoradiotherapy toxicity in lung cancer.

Med (New York, N.Y.)
BACKGROUND: Gut microbiota (GM) predict responses to immune checkpoint inhibitors (ICIs) in patients with advanced lung cancer. However, its role in patients with locally advanced lung cancer undergoing chemoradiotherapy (CRT) combined with consolida...

Computational pathology approach for assessment of prognosis and immunotherapy response in pan-gastrointestinal cancer.

Journal of translational medicine
BACKGROUND: Current cancer staging methods cannot accurately predict survival outcomes and therapeutic benefits in cancer patients. Digital pathomics, a rapidly evolving field, holds significant potential to revolutionize disease evaluation.

Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX.

Breast cancer research : BCR
BACKGROUND: Proper stratification of recurrence risk in breast cancer is crucial for guiding treatment decisions. This study aims to predict the recurrence risk of breast cancer patients using a multimodal deep learning model that integrates multiple...

Predicting outcomes in head and neck cancer using CT images via transfer learning.

BMC medical imaging
BACKGROUND: Accurate preoperative risk stratification for patients with head and neck (H&N) cancer remained a critical challenge, as long-term survival rates are poor despite aggressive multimodality treatment. While deep learning models showed promi...

Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting.

BMC primary care
BACKGROUND: Establishing risk factors associated with severity and prognosis in the early stages of the disease is important to identify patients who need specialized care. Creating new clinical tools to improve health decisions and outcomes in the p...

A prognostic model for gastric cancer constructed by multiple machine learning algorithms.

Journal of molecular histology
Gastric cancer (GC) is a highly heterogeneous disease that requires highly accurate prognostic models. Machine learning is a powerful tool for identifying predictive biomarkers and developing prognostic models. Here, we aim to integrate bioinformatic...

Predicting one-year overall survival in patients with AITL using machine learning algorithms: a multicenter study.

Scientific reports
Angioimmunoblastic T-cell lymphoma (AITL) is a life-threatening hematological malignancy. For patients with poor prognosis, especially those with expected survival less than 1 year, the benefits from traditional regimens are extremely limited. Theref...

Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study.

Scientific reports
Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric mag...