Cervical cancer is one of the most commonly diagnosed cancers worldwide, and it is particularly prevalent among women living in developing countries. Traditional classification algorithms often require segmentation and feature extraction techniques t...
Diabetes mellitus refers to a collection of metabolic disorders that affect the way carbohydrates are processed in the body. It is a prominent worldwide health issue. Precise and reliable decision-making methods are critical for identifying the most ...
With the escalating demand for exploration within confined spaces, bionic design methodologies have attracted considerable attention from researchers, primarily due to the intrinsic limitations of human access to hazardous environments. However, cont...
Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial radionuclides, and radiation generated by human activities. These radionuclides can infiltrate the human body through various pathways, potentially lead...
Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiomics data of STAD patients in The Cancer Genome Atlas (TCGA)-STAD cohort, which included mRNA, microR...
Numerous studies have proven the potential of deep learning models for classifying wildlife. Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade. Although deep learning mode...
The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still re...
Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI)...
Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability a...
The classification of chronic diseases has long been a prominent research focus in the field of public health, with widespread application of machine learning algorithms. Diabetes is one of the chronic diseases with a high prevalence worldwide and is...
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