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404 articles for “anal disease”
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Pharmacological Management of Parkinson’s Disease: Current Therapies and Emerging Treatments
Abstract: Objective: Parkinson's disease, behind Alzheimer's, is the second most common neurodegenerative ailment and a major cause of neurological morbidity worldwide. Clinical diagnosis is made, and current management is limited to symptomatic treatments, with levodopa remaining the cornerstone of pharmaceutical therapy. In certain patient groups, deep brain stimulation of specific basal ganglia targets can provide significant clinical relief. There are currently no proven disease-modifying medicines in clinical use that can halt …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 1, 2023 · pp. 27–39 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Harnessing IoT and Sensor Technologies for Smart Agriculture: A Path Towards Viksit Bharat
Abstract: The integration of Internet of Things (IoT) and sensor technologies is redefining the landscape of Indian agriculture, serving as a catalyst for achieving the ambitious vision of Viksit Bharat (Developed India). Indian agriculture faces significant challenges such as resource scarcity, climate variability, and fragmented supply chains, which hinder productivity and sustainability. IoT-based solutions offer innovative approaches to address these critical issues by enabling smart irrigation systems, real-time field monitoring, precision …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 2, 2025 · pp. 38–45 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Uncovering the Comparative Efficacy of Antiviral Drugs and Caricapapaya Phytocompound as VP2H inhibitors in Ebola virus: An Insilico Molecular Docking Analysis
Abstract: The Ebola virus is a fatal disease that transmits from wild animals to humans. Infected individuals' body fluids such as spit, blood, perspiration, faeces, blood, saliva, breast milk, sperm, or fomites can transmit Ebola. Adhesion to cell membranes and penetration into the host organism are essential aspects in viral growth. The presence of VP24, as well as nucleoproteins and structural proteins, is necessary for nucleocapsid formation and integration. The inhibition …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 1, Issue 2, 2023 · pp. 62–78 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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In Silico Analysis and Docking Study of the Active Phytocompounds of Bacopa monnieri Against Alzheimer Disease
Abstract: Objective: Alzheimer’s is a neurodegenerative disease and is the cause of 60–70% of cases of dementia. It infected a million people worldwide. An effort was undertaken to explore the potential of natural compounds found in Bacopa monnieri, a plant renowned for its extensive medicinal properties in Indian Ayurveda, to combat the disease. This was achieved through molecular docking studies, evaluation of drug-likeness, and comprehensive ADME (absorption, distribution, metabolism, and excretion) …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 1–13 Read article
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Drugs for Alzheimer’s Disease from Salix Alba Discovered Computationally Utilizing Virtual Screening and Docking against 1b41 Protein
Abstract: Objective : The of this research is to evaluate the feasibility of using molecular docking techniques to identify novel acetylcholinesterase, a key enzyme implicated in the pathogenesis of Alzheimer’s disease, a neurodegenerative disorder with a gradual but steady progression to death, due to the gradual accumulation of beta-plaques and neurofibrillary tangles, as well as a decline in acetylcholine levels. Due to its function in converting acetylcholine into acyl and choline …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 07–19 Read article
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MediSense AI - Smart Health Analysis System
Abstract: MediSense AI is a revolutionary health analysis system that empowers users by transforming complex medical data into understandable insights. This platform utilizes advanced technologies, particularly natural language processing and machine learning, to make intricate medical terminologies accessible to individuals without a healthcare background. Leveraging Llama 3, a cutting-edge AI model developed by Meta AI, the system can analyze various forms of medical data, including the ability for users to upload …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 20–30 Read article
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Editorial: Advancements in Movement Analysis for Understanding Neurological Disorders
Abstract: Neurological disorders pose a significant challenge, demanding innovative approaches for accurate diagnosis, effective treatment, and deeper understanding. Movement analysis emerges as a powerful tool, offering a quantitative window into the complexities of motor function. This editorial delves into the transformative impact of movement analysis on neurological research and clinical practice. Traditional diagnostic methods, reliant on subjective observations, often miss subtle motor impairments, particularly in early disease stages. Movement analysis tackles …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 28–32 Read article
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Engineering Anti-Tau Monoclonal Antibodies for Alzheimer’s Disease and Parkinsonian Tauopathies: A Biotechnological Perspective
Abstract: Neurodegenerative disorders such as Alzheimer’s disease and Parkinson’s disease are characterized by progressive neuronal loss associated with abnormal protein aggregation. Among these, tauopathies are defined by the accumulation of hyperphosphorylated tau protein, which plays a central role in disease progression. Advances in biotechnology have enabled the development of anti-tau monoclonal antibodies (mAbs) as promising therapeutic agents aimed at neutralizing pathological tau species and inhibiting their propagation. This review provides a …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Role of Gastric Receptors in Gastrointestinal Disorder
Abstract: The established and potential roles of cholecystokinin1 and cholecystokinin2 receptors in gastrointestinal and metabolic diseases are analyzed, along with findings from human studies involving agonists and antagonists. While there is considerable evidence implicating cholecystokinin1R in various diseases such as pancreatic disorders, motility disorders, tumor growth, satiety regulation, and cholecystokinin-deficient states, its specific role in these conditions remains ambiguous. Conversely, the role of cholecystokinin2R in physiological (e.g., atrophic gastritis) and pathological …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 2, Issue 2, 2024 · pp. 37–49 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article