AIMC Topic: Heuristics

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A Frame-Based NLP System for Cancer-Related Information Extraction.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep le...

Artificial intelligence-enabled healthcare delivery.

Journal of the Royal Society of Medicine
In recent years, there has been massive progress in artificial intelligence (AI) with the development of deep neural networks, natural language processing, computer vision and robotics. These techniques are now actively being applied in healthcare wi...

A Novel Teaching-Learning-Based Optimization with Error Correction and Cauchy Distribution for Path Planning of Unmanned Air Vehicle.

Computational intelligence and neuroscience
Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning phenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and the...

Rough sets and Laplacian score based cost-sensitive feature selection.

PloS one
Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feat...

Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

Applied clinical informatics
Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with s...

A pattern learning-based method for temporal expression extraction and normalization from multi-lingual heterogeneous clinical texts.

BMC medical informatics and decision making
BACKGROUND: Temporal expression extraction and normalization is a fundamental and essential step in clinical text processing and analyzing. Though a variety of commonly used NLP tools are available for medical temporal information extraction, few wor...

Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer.

Endoscopy
BACKGROUND AND STUDY AIMS: Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificia...

Adaptive neuro-heuristic hybrid model for fruit peel defects detection.

Neural networks : the official journal of the International Neural Network Society
Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the develo...

A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women.

Osteoarthritis and cartilage
OBJECTIVE: Knee osteoarthritis (OA) is among the higher contributors to global disability. Despite its high prevalence, currently, there is no cure for this disease. Furthermore, the available diagnostic approaches have large precision errors and low...

Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval.

Neural networks : the official journal of the International Neural Network Society
Simulation and positioning are very important aspects of computer aided engineering. To process these two, we can apply traditional methods or intelligent techniques. The difference between them is in the way they process information. In the first ca...