AIMC Topic: Prognosis

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Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.

European journal of nuclear medicine and molecular imaging
PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in ...

An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer.

BMC cancer
BACKGROUND AND OBJECTIVE: In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artifi...

Computational pathology in cancer diagnosis, prognosis, and prediction - present day and prospects.

The Journal of pathology
Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging fro...

Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.

European radiology
OBJECTIVES: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in comparison to the Eastern Cooperative Oncology Group (ECOG) score for survival of patients with advanced pancreatic cancer treated with high-intensity ...

Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis.

World neurosurgery
BACKGROUND: Meningiomas are common intracranial tumors. Machine learning (ML) algorithms are emerging to improve accuracy in 4 primary domains: classification, grading, outcome prediction, and segmentation. Such algorithms include both traditional ap...

Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.

Current rheumatology reports
PURPOSE OF REVIEW: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and pat...

A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algor...

Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response.

The Journal of pathology
In recent years, the application of advanced analytics, especially artificial intelligence (AI), to digital H&E images, and other histological image types, has begun to radically change how histological images are used in the clinic. Alongside the re...

Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals.

PloS one
BACKGROUND: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate ...