Pneumonia is a deadly disease affecting millions worldwide, caused by microorganisms and environmental factors. It leads to lung fluid build-up, making breathing difficult, leading cause of death. Early detection treatment are crucial for preventing severe outcomes. Chest X-rays commonly used diagnoses due their accessibility low costs; however, detecting pneumonia through challenging. Automated methods needed, machine learning can solve complex computer vision problems in medical imaging....

This paper explores the effectiveness of Particle Swarm Classification (PSC) for a classification task in field educational data mining. More specifically, it proposes PSC to design model capable classifying questions into six cognitive levels Bloom's taxonomy. To this end, novel specialized initialization mechanism based on Rocchio Algorithm (RA) mitigate adverse effects curse dimensionality performance. Furthermore, RA-based classification, several feature selection approaches are...

Questioning is widely acknowledged as an effective instructional strategy used by teachers in their interaction with students for variety of purposes. In educational practices, the analysis classroom questions asked particular benefits. This paper investigates effectiveness machine learning techniques on analyzing teacher's automatically classifying them into different cognitive levels identified Bloom's taxonomy. More specifically, this reports three most text classification: k-Nearest...

Left ventricle (LV) segmentation using a cardiac magnetic resonance imaging (MRI) dataset is critical for evaluating global and regional functions diagnosing cardiovascular diseases. LV clinical metrics such as volume, mass ejection fraction (EF) are frequently extracted based on the from short-axis MRI images. Manual to assess tedious time-consuming medical experts diagnose pathologies. Therefore, fully automated technique required assist in working more efficiently.This paper proposes...

Abstract In outcome‐based academic programs, Program Educational Objectives (PEOs) and Student Outcomes (SOs) are two cores around which all programs’ components processes revolve. Needless to say, the PEOs‐SOs mapping is very critical for program success and, therefore, a deep understanding of PEOs, SOs, their intra/inter‐correlations important effective program's decisions making. this context, paper proposes data mining‐based approach discover hidden knowledge correlations in engineering...

This paper presents a novel application of data mining techniques to guide academic programs design and assessment. More specifically, it propose using association rule discover set rules that govern the relationship between two core components an program, program educational objectives (PEOs) students outcomes(SOs). As case study, this demonstrates how are applied mine mapping PEOs predefined SOs adopted by American Board for Engineering Technology-Engineering Accreditation Commission...

This paper presents a new application of data mining techniques, particularly text mining, to analyze educational questions asked by teachers in classrooms. More specifically, it reports on the performance four machine learning techniques and feature selection approaches classification teacher's into different cognitive levels identified Bloom's taxonomy. In doing so, dataset has been collected classified manually levels. Preprocessing steps have applied convert suitable representation....

Cloud computing provides a ubiquitous data storage and access mechanism for organizations, industries, smart grids to facilitate their operations. However, the concern in cloud systems is secure control toward authentication sensitive data, such as electric vehicles (EVs) requesting information attending charging service. Consequently, denying an authentic user’s request will result delaying requested service, thereby leading service inefficiency. The role-based (RBAC) plays crucial role...

This paper introduces machine learning approaches to a new application in the field of education. More specifically, it explores effectiveness three approaches, namely, k-nearest neighbours, naïve Bayes, and support vector machines with term frequency as selection approach, on task evaluating teaching by classifying teachers’ classroom questions into different cognitive levels identified Bloom’s taxonomy. In doing so, dataset has been collected annotated manually levels. Several steps...

This paper explores the effectiveness of Particle Swarm Classification technique for tackling a classification problem in an emergent data mining field, called Educational Data Mining. More specifically, it applies to classify set teachers' classroom questions into cognitive levels Bloom's taxonomy. Furthermore, high dimensionality enables investigating particle swarm dimensional domains. In doing so, has been collected and annotated manually with taxonomy levels. Preprocessing steps have...

Epilepsy is a common neurological disorder worldwide and antiepileptic drug (AED) therapy the cornerstone of its treatment. It has laudable aim achieving seizure freedom with minimal, if any, adverse reactions (ADRs). Too often, AED treatment long-lasting journey, in which ADRs have crucial role administration. Therefore, from pharmacovigilance perspective, detecting AEDs task utmost importance. Typically, this accomplished by analyzing relevant data spontaneous reporting systems. Despite...

In today’s world, the healthcare industry faces difficulties like a scarcity of professionals, ageing, and rising costs. Also classification decision making process using data generated via electronic health sensors is major concern. fields research medical services, artificial intelligence (AI) widely employed. However, correct estimate for various illnesses significant issue. The implementation new hybrid (AI)-based classifier helping prediction diagnosis in patients with chronic cancer...

This paper proposes a new variant of Particle Swarm Optimization (PSO), dubbed CentroidPSO, to tackle data classification problem in high dimensional domains. It is inspired by the center-based sampling theory, which states that center region search space contains points with higher probability be closer optimal solution. The experimental results show striking performance CentroidPSO as compared standard PSO, four closely related PSO variants, and three recent evolutionary computation...

Coronary artery bifurcation lesion is an epicardial stenosis that, when compared to non-bifurcation lesions, poses a greater risk of adverse events and can compromise prognosis. This study aims investigate the clinical efficacy different stenting techniques, particularly in terms their immediate, short-term, intermediate, long-term outcomes patients with true lesions.

With the increasing availability of wearable devices for data collection, studies in human activity recognition have gained significant popularity. These report high accuracies on k-fold cross validation, which is not reflective their generalization performance but a result inappropriate split testing and training datasets, causing these models to evaluate same subjects that they were trained on, making them subject-dependent. This study comparatively discusses this validation approach with...

In outcome-based academic programs, Program Education Objects (PEOs) are the key pillars on which program components built. They articulated linguistically as broad statements of graduates’ professional and career accomplishments within a few years graduation. Moreover, PEOs mapped into set skills attributes known Learning Outcomes (PLOs). It goes without saying that profound understanding is factor in success an program. For this sake, paper proposes data analytics-based approach to examine...

In pharmacovigilance, the detection of adverse drug reactions is a task utmost importance. This paper presents data mining-based method to detect anti-epileptic drugs from dataset patients' reviews collected an online health community. The preprocessed and unigram, bigram, trigram are generated then each extracted with help consumer vocabulary lexicon. Proportional reporting ratio used measure association between reaction antiepileptic drug. A list ranked for validated against Drugs.com...