AIMC Topic: Prognosis

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Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

Journal of consulting and clinical psychology
OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from randomized clinical trials involving strict standardization of treatments, stringent patient exclusion criteria, and careful selection and supervision of st...

Screening key lncRNAs with diagnostic and prognostic value for head and neck squamous cell carcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.

Cancer biomarkers : section A of Disease markers
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer around the world. The aim of this study was to seek the long non-coding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of HNSCC.

[Study of Skip Metastasis to Lateral Lymph Nodes in Low Rectal Cancer].

Gan to kagaku ryoho. Cancer & chemotherapy
We reviewed the clinical records of 302 patients with low rectal carcinoma to evaluate the effectiveness of lateral lymph node(LLN)dissection in cases of skip metastases to the LLN. Patients were divided into 4 groups according to nodal status: group...

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...

The role of artificial intelligence and machine learning in predicting orthopaedic outcomes.

The bone & joint journal
This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datase...

Prognostic models will be victims of their own success, unless….

Journal of the American Medical Informatics Association : JAMIA
Predictive analytics have begun to change the workflows of healthcare by giving insight into our future health. Deploying prognostic models into clinical workflows should change behavior and motivate interventions that affect outcomes. As users respo...

Predictive analytics in health care: how can we know it works?

Journal of the American Medical Informatics Association : JAMIA
There is increasing awareness that the methodology and findings of research should be transparent. This includes studies using artificial intelligence to develop predictive algorithms that make individualized diagnostic or prognostic risk predictions...

Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation.

Blood advances
Acute graft-versus-host disease (aGVHD) is 1 of the critical complications that often occurs following allogeneic hematopoietic stem cell transplantation (HSCT). Thus far, various types of prediction scores have been created using statistical calcula...

Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.

World journal of gastroenterology
BACKGROUND: Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, the...