Coronavirus (CoV) disease 2019 (COVID-19) is a severe pandemic affecting millions worldwide. Due to its rapid evolution, researchers have been working on developing diagnostic approaches to suppress its spread. This study presents an effective automated approach based on genomic image processing (GIP) techniques to rapidly detect COVID-19, among other human CoV diseases, with high acceptable accuracy. The GIP technique was applied as follows: first, genomic graphical mapping techniques were used to convert the genome sequences into genomic grayscale images. The frequency chaos game

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and poses a major burden on the human health worldwide. At the moment, treatment of CRC consists of surgery in combination with (neo)adjuvant chemotherapy and/or radiotherapy. More recently, immune checkpoint blockers (ICBs) have also been approved for CRC treatment. In addition, recent studies have shown that radiotherapy and ICBs act synergistically, with radiotherapy stimulating the immune system that is activated by ICBs. However, both treatments are also associated with severe toxicity and efficacy issues, which can

Capturing the diverse microbiota from healthy and/or stress resilient plants for further preservation and transfer to unproductive and pathogen overloaded soils, might be a tool to restore disturbed plant-microbe interactions. Here, we introduce Aswan Pink Clay as a low-cost technology for capturing and storing the living root microbiota. Clay chips were incorporated into the growth milieu of barley plants and developed under gnotobiotic conditions, to capture and host the rhizospheric microbiota. Afterward, it was tested by both a culture-independent (16S rRNA gene metabarcoding) and

The development of artificial intelligence (AI) provided powerful assistant tools for humans in various aspects. Healthcare is rapidly evolving, with AI playing a crucial role in improving patient care. The extensive use of AI in Clinical Decision Support Systems (CDSS) enables providing real-time evidence-based recommendations to healthcare professionals at the point of Care. The AI chatbot ChatGPT proved its ability to solve several natural language processing tasks. One notable advancement is the integration of ChatGPT into Clinical Decision Support Systems. ChatGPT, despite not being

Precise Recitation of Holy Quran is a religious duty that must be performed with great care. Tajweed rules are constructed to guide the reader to utter the Holy Quran text as it was originally uttered by prophet Muhammad. An automatic pattern detection algorithm is implemented to allocate basic Tajweed rules. The rules addressed in this paper, are Madd, Noon Sakinah, Tanween and Meem Sakinah rules. These rules are characterized by well-defined uttered style. The rules studied in this paper, were allocated at 487 positions in forty verses of Surat El-Anfal of Sheikh El-Hosary's recitation. Data

One of the most fatal potentially life-threatening medical condition that increases the mortality in pediatric populations is pediatric sepsis. Unfortunately, the improper control of such disease can lead to tissue damage and organ dysfunction because of the overwhelming the human body's response to an infection. Therefore, early recognition and intervention can clearly improve outcome for infants and children with conditions that lead to sepsis before the admission to the intensive care unit (ICU). Accordingly, 17 informative differential expressed genes have been selected using a nature

Nuclei segmentation is a critical task in biological image analysis, with numerous applications in cancer diagnosis, grading, staging, and treatment planning. However, this task is challenging, particularly when dealing with low-resolution and low signal-to-noise ratio microscopy images. Segmentation problems arise, such as touching and missing cells, which make the process even more challenging. Deep learning models, including Attention U-Net and TransUNet, have demonstrated exceptional performance in medical image segmentation. Nonetheless, the choice of optimizer can significantly impact

Genomic microarray databases encompass complex high dimensional gene expression samples. Imbalanced microarray datasets refer to uneven distribution of genomic samples among different contributed classes which can negatively affect the classification performance. Therefore, gene selection from imbalanced microarray dataset can give rise to misleading, and inconsistent nominated genes that would alter the classification performance. Such unsatisfactory classification performance is due to the skewed distribution of the samples across the microarrays toward the majority class. In this paper, we

Current Autism Spectrum Disorder (ASD) diagnosis methods exhibit some limitations as they are based on clinical interviews and observations of behaviors, characteristics, and abilities. Moreover, considering the current challenges in identifying the causes and mechanisms associated with ASD, there is an essential need for automated techniques capable of providing an accurate classification between ASD and typically developed (TD). In this paper, we present a convolutional neural network model that can differentiate ASD from TD. This proposed system is trained and validated on the well-known

correct understanding of the Holy Quran is an essential duty for all Muslims. Tajweed rules guide the reciter to perform Holy Quran reading exactly as it was uttered by Prophet Muhammad peace be upon him. This work focused on the recognition of one Quranic recitation rule. Qalqalah rule is applied to five letters of the Arabic Alphabet (Baa/Daal/Jeem/Qaaf/Taa) having sukun vowelization. The proposed system used the Mel Frequency Cepstral Coefficients (MFCC) as the feature extraction technique, and the Convolutional Neural Networks (CNN) model was used for recognition. The available dataset