AI Medical Compendium Topic:
Fuzzy Logic

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An Ensemble Model With Clustering Assumption for Warfarin Dose Prediction in Chinese Patients.

IEEE journal of biomedical and health informatics
The prediction of daily stable warfarin dosage for a specific patient is difficult. To improve the predictive accuracy and to build a highly accurate predictive model, we developed an ensemble learning method, called evolutionary fuzzy c-mean (EFCM) ...

Efficient Segmentation of Brain Tumor Using FL-SNM with a Metaheuristic Approach to Optimization.

Journal of medical systems
Nowadays, automatic tumor detection from brain images is extremely significant for many diagnostic as well as therapeutic purposes, due to the unpredictable shape and appearance of tumors. In medical image analysis, the automatic segmentation of tumo...

Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps.

IEEE/ACM transactions on computational biology and bioinformatics
While protein-DNA interactions are crucial for a wide range of cellular functions, only a small fraction of these interactions was annotated to date. One solution to close this annotation gap is to employ computational methods that accurately predict...

Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence.

The Science of the total environment
Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO energy source. Gasification of bio...

An IoT Based Predictive Modelling for Predicting Lung Cancer Using Fuzzy Cluster Based Segmentation and Classification.

Journal of medical systems
In this paper, we propose a new Internet of Things (IoT) based predictive modelling by using fuzzy cluster based augmentation and classification for predicting the lung cancer disease through continuous monitoring and also to improve the healthcare b...

Fuzzy logic based approaches for gene regulatory network inference.

Artificial intelligence in medicine
The rapid advancements in high-throughput techniques have fueled large-scale production of biological data at very affordable costs. Some of these techniques are microarrays and next-generation sequencing that provide genome level insight of living c...

CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm.

Artificial intelligence in medicine
Liver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the liver with the same intensity, high noise and large variance of tumors. The...

Blind Channel and Data Estimation Using Fuzzy Logic-Empowered Opposite Learning-Based Mutant Particle Swarm Optimization.

Computational intelligence and neuroscience
Multiple-input and multiple-output (MIMO) technology is one of the latest technologies to enhance the capacity of the channel as well as the service quality of the communication system. By using the MIMO technology at the physical layer, the estimati...

MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Generally the segmentation refers, the partitioning of an image into smaller regions to identify or locate the region of abnormality. Even though image segmentation is the challenging task in medical applications, due to contrary image, local observa...

Image Registration based Cervical Cancer Detection and Segmentation Using ANFIS Classifier.

Asian Pacific journal of cancer prevention : APJCP
Cervical cancer is the leading cancer in women around the world. In this paper, Adaptive Neuro Fuzzy Inference System (ANFIS) classifier based cervical cancer detection and segmentation methodology is proposed. This proposed system consists of the fo...