Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding student exploring utilizing educational data using machine mining techniques. Modern academic institutions operate highly competitive complex environment. Analyzing performance, providing high-quality education, strategies evaluating students’ future actions are among...

Predicting protein complexes from protein-protein interaction data is becoming a fundamental problem in computational biology. The identification and characterization of implicated are crucial to the understanding molecular events under normal abnormal physiological conditions. On other hand, large datasets experimentally detected interactions were determined using High-throughput experimental techniques. However, usually liable contain number spurious interactions. Therefore, it essential...

AI in medicine has been recognized by both academia and industry revolutionizing how healthcare services will be offered providers perceived all stakeholders. We aim to review recent tendencies building applications for foster its further development outlining obstacles. Sub-objectives: (1) highlight techniques that we have identified as key areas of AI-related research healthcare; (2) offer guidelines on reliable AI-based CAD-systems medicine; (3) reveal open questions, challenges,...

A novel coronavirus (COVID-19) has taken the world by storm. The disease spread very swiftly worldwide. timely clue which includes estimation of incubation period among COVID-19 patients can allow governments and healthcare authorities to act accordingly. undertake a review critical appraisal all published/preprint reports that offer an periods for COVID-19. This research looked relevant published articles between dates December 1, 2019, April 25, 2020, i.e. those were related period. Papers...

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such can be processed to enhance these organizations’ decisions real time. However, storing and processing large varied datasets (known as big data) is challenging do In machine learning, streaming feature selection has always been considered superior technique for selecting the relevant subset features from highly dimensional thus reducing learning complexity. literature, refers that arrive...

Chest radiography is a significant diagnostic tool used to detect diseases afflicting the chest. The automatic detection techniques associated with computer vision are being adopted in medical imaging research. Over last decade, several remarkable advancements have been made field of diagnostics application deep learning techniques. Various automated systems proposed for rapid pneumonia from chest X-rays. Although algorithms currently available detection, detailed review summarizing...

Background Despite the necessity, there is no reliable biomarker to predict disease severity and prognosis of patients with COVID-19. The currently published prediction models are not fully applicable clinical use. Objectives To identify predictive biomarkers COVID-19 justify their threshold values for stratification risk deterioration that would require transferring intensive care unit (ICU). Methods study cohort (560 subjects) included all consecutive admitted Dubai Mediclinic Parkview...

Precise classification of histopathological images is crucial to computer-aided diagnosis in clinical practice. Magnification-based learning networks have attracted considerable attention for their ability improve performance classification. However, the fusion pyramids at different magnifications an under-explored area. In this paper, we proposed a novel deep multi-magnification similarity (DSML) approach that can be useful interpretation framework and easy visualize feature representation...

The angiogenesis inhibitor, sorafenib, remains the only available therapy of hepatocellular carcinoma (HCC). Only recently patents VEGF receptors-3 inhibitors are developed. Thus, a novel approach against HCC is essential for better therapeutic outcome.The aims this study were to examine chemopreventive action saffron's main biomolecule, crocin, chemically-induced liver cancer in rats, and explore mechanisms by which crocin employs its anti-tumor effects.We investigated anti-cancer effect on...

Nowadays, airline ticket prices can vary dynamically and significantly for the same flight, even nearby seats within cabin. Customers are seeking to get lowest price while airlines trying keep their overall revenue as high possible maximize profit. Airlines use various kinds of computational techniques increase such demand prediction discrimination. From customer side, two models proposed by different researchers save money customers: that predict optimal time buy a minimum price. In this...

Accurate prediction of a newborn's birth weight (BW) is crucial determinant to evaluate the health and safety. Infants with low BW (LBW) are at higher risk serious short- long-term outcomes. Over past decade, machine learning (ML) techniques have shown successful breakthrough in field medical diagnostics. Various automated systems been proposed that use maternal features for LBW prediction. However, each system uses different classification estimation. Therefore, this paper provides detailed...

Evaluating the previous work is an important part of developing segmentation methods for image analysis techniques.The aim this paper to give a review digital problems represent great challenges computer vision.The wide range vision may make good use segmentation.This study and evaluate different techniques.We discuss main tendency each algorithm with their applications, advantages disadvantages.This useful determining appropriate improving accuracy performance also objective, which...

The design of novel inhibitors to target BACE1 with reduced cytotoxicity effects is a promising approach treat Alzheimer's disease (AD). Multiple clinical drugs and antibodies such as AZD3293 Solanezumab are being tested investigate their therapeutical potential against AD. current study explores the binding pattern proteins β-secretase (BACE1) mid-region amyloid-beta (Aβ) (PDBIDs: 2ZHV & 4XXD), respectively using molecular docking dynamic simulation (MD) approaches. results show that binds...

Today, artificial intelligence has proliferated to reach almost every wing of daily life, perhaps one the most sensitive these being education. While teaching, insofar as it involves training human minds, is still mostly a form art rather than regular science, taking up this elitist job by computers triggered much debate and controversy, involving teaching community select corporate AI giants who strive create capable better humans. This paper surveys relevant studies carried out in field...

Floods are among the devastating types of disasters in terms human life, social and financial losses. Authoritative data from flood gauges scarce arid regions because specific type dry climate that dysfunctions these measuring devices. Hence, media could be a useful tool this case, where wealth information is available online. This study investigates reliability related quality collected media, particularly for an region usage flow limited. The (text, images videos) to event, was analyzed...

Green space is any green infrastructure consisting of vegetation. linked with improving mental and physical health, providing opportunities for social interactions activities, aiding the environment. The quality refers to condition space. Past machine learning-based studies have emphasized that littering, lack maintenance, dirtiness negatively impact perceived These methods assess spaces their qualities without considering human perception spaces. Domain-based methods, on other hand, are...