AIMC Topic: Prognosis

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Usage of Probabilistic and General Regression Neural Network for Early Detection and Prevention of Oral Cancer.

TheScientificWorldJournal
In India, the oral cancers are usually presented in advanced stage of malignancy. It is critical to ascertain the diagnosis in order to initiate most advantageous treatment of the suspicious lesions. The main hurdle in appropriate treatment and contr...

Oncologic Long-Term Results of Robot-Assisted Minimally Invasive Thoraco-Laparoscopic Esophagectomy with Two-Field Lymphadenectomy for Esophageal Cancer.

Annals of surgical oncology
BACKGROUND: Open transthoracic esophagectomy is the worldwide gold standard in the treatment of resectable esophageal cancer. Robot-assisted minimally invasive thoraco-laparoscopic esophagectomy (RAMIE) for esophageal cancer may be associated with re...

Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

The international journal of neuropsychopharmacology
BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographi...

Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning.

Radiation oncology (London, England)
BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the jud...

Prediction of effluent concentration in a wastewater treatment plant using machine learning models.

Journal of environmental sciences (China)
Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentratio...

Variable importance and prediction methods for longitudinal problems with missing variables.

PloS one
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...

Bridging a translational gap: using machine learning to improve the prediction of PTSD.

BMC psychiatry
BACKGROUND: Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivor...

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Annals of surgical oncology
BACKGROUND: The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, convent...