Search
53 articles for “data profiling”
-
Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
-
AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
-
Deciphering Th-Related Gene Interactions in Chronic Spontaneous Urticaria: Bioinformatics Insights and Drug Affinity Exploration
Abstract: Objective: There has been a great deal of interest in how inflammatory dermatosis and The cell interact, but the etiopathogenesis of chronic spontaneous urticaria (CSU) is still inadequately comprehended. Through bioinformatics techniques, the purpose of this work is to elucdate the molecular mechanism underlying Th-related genes in CSU and seeks to find the highest affinity drug. Methods: The CSU RNA expression profiling dataset provided the basis for the investigation. The …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 1, 2024 · pp. 1–15 Read article
-
The Importance of DNA Profiling Today
Abstract: DNA profiling has changed a lot of sectors, from health and criminal justice to ancestry research and animal conservation. It is one of the most important scientific instruments of our time. This technique makes it possible to identify people, analyse family relationships, and learn more about biology by looking at unique genetic markers in a person's DNA. DNA profiling has changed the way forensic science works by making it easier …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
-
Geological and Geophysical Studies of the Ninety East Ridge: A Brief Review
Abstract: The Indian Ocean serves as a unique laboratory for studying the impact of both global and regional stressors on environmental changes over various geological epochs. Its distinct hydrological conditions and geographical location make it an ideal focal point for research into these phenomena. Of particular interest within the Indian Ocean is the Ninety East Ridge (NER), which holds significance as the world's longest linear rise. Researchers have long hypothesized that …
Published in International Journal of Marine Life · Vol. 1, Issue 1, 2024 · pp. 8–19 Read article
-
Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
-
Dimensionality Reduction Techniques and their Applications in Cancer Classification: A Comprehensive Review
Abstract: Dimensionality reduction techniques have become a vital tool in the investigation of high-dimensional data like gene expression profiles in cancer research. Here is a review, we deliver a comprehensive overview of dimensionality reduction techniques and their applications in cancer classification. Firstly, we introduce the concepts and approaches of dimensionality reduction, and after that, we explore several methods for decreasing dimensionality. These techniques include Linear Discriminant Analysis (LDA), Principal Component Analysis …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 35–45 Read article
-
Experimental Study of Roughness Analysis of AISI 316L Material using Fiber and CO2 LBM
Abstract: Laser beam machines have gained significant attention as a precise and versatile method for cutting and shaping materials in various industries. This study investigates the surface roughness characteristics of SS 316L, a commonly used stainless steel, when subjected to laser beam machining using both fiber and CO2 laser sources. The aim of this research is to compare the effects of these two laser types on the final surface finish of …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 12–21 Read article
-
Quality of Sleep Among Patients with Chronic Renal Failure
Abstract: Renal failure is the partial or complete impairment of kidney function. Inability to eliminate metabolic waste products and water, along with functional disruptions in all bodily systems, result in the condition known as renal failure. Renal failure can be categorized as either acute or chronic. Chronic renal failure refers to the gradual and irreversible deterioration of the nephrons in both kidneys. It is characterized by either kidney damage or a …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 1, Issue 1, 2023 · pp. 22–28 Read article
-
Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
-
SiRNA-Based Multivalent Vaccines: A Systematic Review of Potential Risks, Benefits, and Future Applications
Abstract: Background: Small interfering RNA (SiRNA) technology represents a promising innovation in vaccine development, especially for multivalent vaccines that can target multiple pathogens or antigenic variants simultaneously. siRNA-based vaccines offer a unique mechanism to induce specific immune responses, presenting an adaptable and potentially powerful tool for tackling infectious diseases and cancer. Methods: This systematic review synthesizes recent studies on siRNA multivalent vaccines, focusing on their immunogenicity, safety, and effectiveness. We reviewed …
Published in International Journal of Vaccines · Vol. 2, Issue 1, 2025 · pp. 43–49 Read article
-
Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
-
A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
-
Vaccination in the Era of Precision Medicine: Tailoring Immunization Strategies for Individual Risk Profiles
Abstract: The introduction of precision medicine has caused a paradigm change in the vaccine landscape. Conventionally, vaccination programmes have been homogeneous, targeting immunity at the population level without taking into consideration the individual differences in immune response and vulnerability to diseases that can be prevented by vaccination. However, a more individualised approach to immunisation has been made possible by current developments in genetics, immunology, and data analytics. Within the context of …
Published in International Journal of Vaccines · Vol. 1, Issue 2, 2024 · pp. 32–47 Read article
-
Morphological Heterogeneity and Ethnic Patterning of Anthropometric Traits in Ethiopian Inter-Scholastic Athletes
Abstract: Introduction: Anthropometric characteristics such as body size, proportions, and composition are fundamental determinants of morphological suitability for sport. Ethiopia’s significant ethnic diversity suggests potential variability in these traits; however, systematic data on anthropometric differences among adolescent athletes from different ethnic and demographic backgrounds remain limited. Understanding these variations is critical for talent identification and sports specialization at the school level. Methods: A cross-sectional study was conducted among inter-scholastic athletes representing …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 25–34 Read article
-
Personalized Nutrition and Exercise: Pioneering the Path to Precision Medicine
Abstract: Preventive healthcare is about to undergo a major shift thanks to the personalised exercise and nutrition paradigm, which is based on precision medicine concepts. In order to create tailored recommendations for improving health outcomes and preventing chronic diseases, this article explores the integration of genetic profiling, metabolic evaluation, and lifestyle factors. A person's response to food and exercise depends heavily on genetic and metabolic variances, which emphasises the need of …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 42–46 Read article
-
Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
-
Evolution and Impact of Forensic DNA Typing in Modern Investigation
Abstract: Forensic DNA typing is sometimes called DNA fingerprinting. Immigration, paternity, and criminal investigations use forensic DNA typing. Forensic genetics today includes bodily fluid identification, fast DNA analysis, forensic microbiology, and phenotypic profiling. Human cells contain DNA, a molecular code. Human DNA sequences are 99.9% the same in everyone. Every person has almost 0.1% unique DNA. Forensic experts also worry about this 0.1 percent of DNA that is unique. There are …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 62–66 Read article
-
Harnessing the Growth Potential of Cloud Computing in Agriculture
Abstract: Unlocking the Green Revolution: A Comprehensive Exploration of Cloud Computing Integration in India's Agricultural Landscape. The integration of cloud computing technology in the agricultural sectors of India is poised to play a pivotal role in propelling the nation's holistic development. This paper delves into the dynamic realm of cloud computing, serving as a catalyst for innovation and efficiency in agriculture. By eliminating the need for maintaining expensive computing infrastructure, cloud …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 32–37 Read article
-
A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article