AIMC Topic: Prognosis

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Stroke prognostication for discharge planning with machine learning: A derivation study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Post-stroke discharge planning may be aided by accurate early prognostication. Machine learning may be able to assist with such prognostication. The study's primary aim was to evaluate the performance of machine learning models using admission data t...

Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.

PloS one
OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, ...

Predicting Alzheimer's disease progression using deep recurrent neural networks.

NeuroImage
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more t...

Development and validation of prognosis model of mortality risk in patients with COVID-19.

Epidemiology and infection
This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 Mar...

Development of a Machine Learning Model for Survival Risk Stratification of Patients With Advanced Oral Cancer.

JAMA network open
IMPORTANCE: A tool for precisely stratifying postoperative patients with advanced oral cancer is crucial for the treatment plan, such as intensifying or deintensifying the regimen to improve their quality of life and prognosis.

Survivability modelling using Bayesian network for patients with first and secondary primary cancers.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Multiple primary cancers significantly threat patient survivability. Predicting the survivability of patients with two cancers is challenging because its stochastic pattern relates with numerous variables.

Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

Clinical and experimental nephrology
BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min 1.73 m). There is difference in prevalence of CKD, racial differences, economic development, genetic, and environmental backgrounds between China and ...

Effectiveness of Artificial Intelligence Applications Designed for Endodontic Diagnosis, Decision-making, and Prediction of Prognosis: A Systematic Review.

The journal of contemporary dental practice
AIM: With advancements in science and technology, there has been phenomenal developments in the application of neural networks in dentistry. This systematic review aimed to report on the effectiveness of artificial intelligence (AI) applications desi...

Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.

Remaining Useful Life Estimation Using Deep Convolutional Generative Adversarial Networks Based on an Autoencoder Scheme.

Computational intelligence and neuroscience
Accurate predictions of remaining useful life (RUL) of important components play a crucial role in system reliability, which is the basis of prognostics and health management (PHM). This paper proposed an integrated deep learning approach for RUL pre...