AI Medical Compendium Topic:
Prognosis

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Predicting kidney allograft survival with explainable machine learning.

Transplant immunology
INTRODUCTION: Despite significant progress over the last decades in the survival of kidney allografts, several risk factors remain contributing to worsening kidney function or even loss of transplants. We aimed to evaluate a new machine learning meth...

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

Journal of neuro-oncology
PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this...

Prediction of recurrence risk in endometrial cancer with multimodal deep learning.

Nature medicine
Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined pathological and molecular profiling is costly, hampering implementation. Here we developed HECTOR (histopa...

Exploring T-cell exhaustion features in Acute myocardial infarction for a Novel Diagnostic model and new therapeutic targets by bio-informatics and machine learning.

BMC cardiovascular disorders
BACKGROUND: T-cell exhaustion (TEX), a condition characterized by impaired T-cell function, has been implicated in numerous pathological conditions, but its role in acute myocardial Infarction (AMI) remains largely unexplored. This research aims to i...

Predicting the Outcome and Survival of Patients with Spinal Cord Injury Using Machine Learning Algorithms: A Systematic Review.

World neurosurgery
BACKGROUND: Spinal cord injury (SCI) is a significant public health issue, leading to physical, psychological, and social complications. Machine learning (ML) algorithms have shown potential in diagnosing and predicting the functional and neurologic ...

Pathomic model based on histopathological features and machine learning to predict IDO1 status and its association with breast cancer prognosis.

Breast cancer research and treatment
PURPOSE: To establish a pathomic model using histopathological image features for predicting indoleamine 2,3-dioxygenase 1 (IDO1) status and its relationship with overall survival (OS) in breast cancer.

Enhancing cervical cancer prognosis: Integrating machine learning and clinical insights for personalized patient care and improved outcomes.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.

BMC pulmonary medicine
BACKGROUND: Mortality prediction in interstitial lung disease (ILD) poses a significant challenge to clinicians due to heterogeneity across disease subtypes. Currently, forced vital capacity (FVC) and Gender, Age, and Physiology (GAP) score are the t...

Artificial intelligence to predict individualized outcome of acute ischemic stroke patients: The SIBILLA project.

European stroke journal
INTRODUCTION: Formulating reliable prognosis for ischemic stroke patients remains a challenging task. We aimed to develop an artificial intelligence model able to formulate in the first 24 h after stroke an individualized prognosis in terms of NIHSS.