AI Medical Compendium Topic:
Diagnosis, Computer-Assisted

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Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...

Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images.

Scientific reports
Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utilize large volumes of training data, which are not available in many healthcare contexts. For patients with brain tumors, non-invasive diagnosis would r...

Improving CNN training on endoscopic image data by extracting additionally training data from endoscopic videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this work we present a technique to deal with one of the biggest problems for the application of convolutional neural networks (CNNs) in the area of computer assisted endoscopic image diagnosis, the insufficient amount of training data. Based on p...

Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.

Acta cytologica
INTRODUCTION: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, opti...

A Medical Decision Support System to Assess Risk Factors for Gastric Cancer Based on Fuzzy Cognitive Map.

Computational and mathematical methods in medicine
Gastric cancer (GC), one of the most common cancers around the world, is a multifactorial disease and there are many risk factors for this disease. Assessing the risk of GC is essential for choosing an appropriate healthcare strategy. There have been...

Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences.

BMC medical informatics and decision making
BACKGROUND: Computer Aided Diagnostics (CAD) can support medical practitioners to make critical decisions about their patients' disease conditions. Practitioners require access to the chain of reasoning behind CAD to build trust in the CAD advice and...

EEG-Based Epilepsy Recognition via Multiple Kernel Learning.

Computational and mathematical methods in medicine
In the field of brain-computer interfaces, it is very common to use EEG signals for disease diagnosis. In this study, a style regularized least squares support vector machine based on multikernel learning is proposed and applied to the recognition of...

World competitive contest-based artificial neural network: A new class-specific method for classification of clinical and biological datasets.

Genomics
Many data mining methods have been proposed to generate computer-aided diagnostic systems, which may determine diseases in their early stages by categorizing the data into some proper classes. Considering the importance of the existence of a suitable...