AIMC Topic: Algorithms

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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm.

Scientific reports
With the advancement of medical technology, a large amount of complex data on cancers is produced for diagnosing and treating cancers. However, not all this data is useful, as many features are redundant or irrelevant, which can reduce the accuracy o...

Evaluating the performance of random forest, support vector machine, gradient tree boost, and CART for improved crop-type monitoring using greenest pixel composite in Google Earth Engine.

Environmental monitoring and assessment
The development of machine learning algorithms, along with high-resolution satellite datasets, aids in improved agriculture monitoring and mapping. Nevertheless, the use of high-resolution optical satellite datasets is usually constrained by clouds a...

Synthetic Data-Driven Approaches for Chinese Medical Abstract Sentence Classification: Computational Study.

JMIR formative research
BACKGROUND: Medical abstract sentence classification is crucial for enhancing medical database searches, literature reviews, and generating new abstracts. However, Chinese medical abstract classification research is hindered by a lack of suitable dat...

Evaluation of an artificial intelligence-based model in diagnosing periodontal radiographic bone loss.

Clinical oral investigations
OBJECTIVE: To develop an artificial intelligence model based on convolutional neural network for detecting and measuring periodontal radiographic bone loss (RBL).

Development and validation comparison of multiple models for perioperative neurocognitive disorders during hip arthroplasty.

Scientific reports
This study aims to develop optimal predictive models for perioperative neurocognitive disorders (PND) in hip arthroplasty patients, thereby advancing clinical practice. Data from all hip arthroplasty patients in the MIMIC-IV database were utilized to...

Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method.

PloS one
Lung cancer (LC) is a leading cause of cancer-related fatalities worldwide, underscoring the urgency of early detection for improved patient outcomes. The main objective of this research is to harness the noble strategies of artificial intelligence f...

Neural network-based ensemble approach for multi-view facial expression recognition.

PloS one
In this paper, we developed a pose-aware facial expression recognition technique. The proposed technique employed K nearest neighbor for pose detection and a neural network-based extended stacking ensemble model for pose-aware facial expression recog...

Weighted Multi-Modal Contrastive Learning Based Hybrid Network for Alzheimer's Disease Diagnosis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Multiple imaging modalities and specific proteins in the cerebrospinal fluid, providing a comprehensive understanding of neurodegenerative disorders, have been widely used for computer-aided diagnosis of Alzheimer's disease (AD). Given the proven eff...

GatedSegDiff: a gated fusion diffusion model for skin lesion segmentation.

Medical & biological engineering & computing
Skin lesion segmentation is a vital process in skin disease diagnosis, crucial for maintaining diagnostic precision. Despite progress in existing image segmentation methods, challenges remain in handling the fuzzy boundaries of skin lesion areas. To ...

Stagger Network: Rethinking information loss in medical image segmentation with various-sized targets.

Neural networks : the official journal of the International Neural Network Society
Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information. Despite recent efforts using CNNs and ViTs to predict annotations of different scales,...