AIMC Topic: Prognosis

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Classification of Skin Disease using Ensemble Data Mining Techniques.

Asian Pacific journal of cancer prevention : APJCP
Objective: Skin diseases are a major global health problem associated with high number of people. With the rapid development of technologies and the application of various data mining techniques in recent years, the progress of dermatological predict...

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

Journal of affective disorders
BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS) treatment is an important purpose that eliminates financial and psychological consequences of applying inefficient therapy. To achieve this goal we p...

The Use of Deep Learning to Predict Stroke Patient Mortality.

International journal of environmental research and public health
The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a str...

Robust identification of molecular phenotypes using semi-supervised learning.

BMC bioinformatics
BACKGROUND: Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in patient outcomes. Unsupervised ...

Computational approaches and machine learning for individual-level treatment predictions.

Psychopharmacology
RATIONALE: The impact of neuroscience-based approaches for psychiatry on pragmatic clinical decision-making has been limited. Although neuroscience has provided insights into basic mechanisms of neural function, these insights have not improved the a...

Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods.

NMR in biomedicine
Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in t...

Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.

Type-2 Fuzzy PCA Approach in Extracting Salient Features for Molecular Cancer Diagnostics and Prognostics.

IEEE transactions on nanobioscience
Machine learning is becoming a powerful tool for cancer diagnosis and prognosis based on classification using high dimensional molecular data. However, extracting classification features from high-dimensional datasets remains a challenging problem. P...

The Pelvis-First Approach for Robotic Proctectomy in Patients with Redundant Abdominal Colon.

Annals of surgical oncology
BACKGROUND: Robotic surgery is increasingly performed for low rectal cancer.1 A redundant sigmoid colon makes retraction and pelvic dissection challenging. We present a 'pelvis-first' approach to robotic proctectomy where pelvic dissection occurs pri...