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Switch to: References
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Abstract: In an era of rapid technological advancements, artificial intelligence (AI) has transformed surveillance systems, enhancing security capabilities across the globe. However, the deployment of AI-driven surveillance raises significant ethical concerns, particularly in balancing the need for security with the protection of individual privacy. This paper explores the ethical challenges posed by AI surveillance, focusing on issues such as data privacy, consent, algorithmic bias, and the potential for mass surveillance. Through a critical analysis of the tension between security and privacy, (...) |
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Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to the (...) |
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Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a (...) |
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Abstract; As artificial intelligence (AI) technologies become increasingly integrated into various facets of society, their impact on human rights has garnered significant attention. This paper examines the intersection of AI and human rights, focusing on key issues such as privacy, bias, surveillance, access, and accountability. AI systems, while offering remarkable advancements in efficiency and capability, also pose risks to individual privacy and can perpetuate existing biases, leading to potential discrimination. The use of AI in surveillance raises ethical concerns about the (...) |
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Tinnitus is a common condition characterized by the perception of sound in the absence of an external source, with potential negative physical and psychological impacts. Accurate and efficient diagnosis of tinnitus is crucial for appropriate treatment and management. Traditional diagnostic methods have limitations in terms of time, cost, and accuracy. To address these challenges, expert systems have emerged as a promising tool for tinnitus diagnosis. This paper explores the application of expert systems in tinnitus diagnosis, highlighting their potential to improve (...) |
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Malaria is a life-threatening disease spread to humans by some types of mosquitoes. It is mostly found in tropical countries. It is preventable and curable. The infection is caused by a parasite and does not spread from person to person. Symptoms can be mild or life-threatening. Mild symptoms are fever, chills and headache. Severe symptoms include fatigue, confusion, seizures, and difficulty breathing. Infants, children under 5 years, pregnant women, travelers and people with HIV or AIDS are at higher risk of (...) |
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There is no doubt that Computer troubleshooting is important for organizations and companies and for personal use level. Sound cards troubles is one of the most annoying problems in computers. It causes damage and troubles in computers to persons, organizations and firms. Correctly, expert systems can greatly help to avoid damage to these computers. designed to diagnose and troubleshoot issues related to sound cards in computer systems. The expert system is developed using a combination of rule-based and machine learning approaches, (...) |
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Brain tumors pose significant challenges in modern healthcare, with accurate and timely diagnosis crucial for determining appropriate treatment strategies. Artificial intelligence has made significant advancements in recent years. Rule-based expert systems (if-then rule-based systems) have emerged as a promising approach for clinical decision-making in brain tumor diagnosis. In this paper, we present "A CLIPS-Based Expert System for Brain Tumor Diagnosis," which leverages a set of 14 if-then rules to diagnose brain tumors with three possible outcomes: 1) Confirm the diagnosis of (...) |
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Heart palpitations, while often benign, can sometimes be indicative of severe underlying conditions requiring immediate intervention. Accurate and swift diagnosis thus remains a clinical priority. "A CLIPS-Based Expert System for Heart Palpitations Diagnosis" represents a novel approach to addressing this challenge, harnessing the power of artificial intelligence and rule-based expert systems. Specifically, this system applies a suite of 7 if-then rules to evaluate potential heart palpitations causes and assign one of three outcomes: 1) A confirmed diagnosis of heart palpitations, 2) (...) |
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This abstract is a synopsis of the paper "An Expert System for Diagnosing Whooping Cough Using CLIPS." The bacterium Bordetella pertussis causes whooping cough, a highly infectious respiratory ailment with several phases of symptoms. An accurate and timely diagnosis is critical for effective treatment and the avoidance of future transmission. The construction of an expert system for detecting whooping cough using the CLIPS (C Language Integrated Production System) architecture is highlighted in this abstract. The expert system provides standardized and systematic (...) |
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Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which utilizes (...) |
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Warts and verrucas are common skin conditions caused by the human papillomavirus (HPV) infection. They present as raised, rough, or bumpy growths on the hands, feet, or other areas subjected to friction or pressure. Plantar warts exhibit a rough surface with small black dots, while genital warts have a cauliflower-like appearance. Pain or itchiness may accompany these lesions. Factors such as close contact with infected individuals and immune compromise can impact the severity and spread of warts. Diagnosis is primarily based (...) |
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This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction. |
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Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. By employing (...) |
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Diagnosing flatulence involves a thorough assessment of an individual's symptoms, medical history, and, if necessary, the use of diagnostic tests. Healthcare providers gather information about the patient's medical background and conduct a physical examination to identify any signs of gastrointestinal issues. Dietary habits are evaluated, and potential triggers are identified through an elimination diet. Diagnostic tests such as breath tests, stool analysis, or imaging studies may be performed to further investigate the underlying causes of excessive flatulence. Accurate diagnosis is crucial (...) |
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Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) |
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A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) |
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Lung cancer is a serious and deadly disease that affects the lungs, which are responsible for taking in oxygen and expelling carbon dioxide from the body. The disease can develop in any part of the lungs and is usually caused by smoking or exposure to certain chemicals. The main Objective: of this expert system is to provide an accurate diagnosis of lung cancer and the appropriate treatment options. In this paper, Methods: we present the design and implementation of an expert (...) |
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Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based system using (...) |
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Migraine is a complex neurological disorder characterized by recurrent moderate to severe headaches, accompanied by additional symptoms such as nausea, sensitivity to light and sound, and visual disturbances. Accurate and timely diagnosis of migraines is crucial for effective management and treatment. However, the diverse range of symptoms and overlapping characteristics with other headache disorders pose challenges in the diagnostic process. In this research, we propose the development of an expert system for migraine diagnosis using artificial intelligence and the CLIPS (C (...) |
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Abstract: The Knowledge-Based System for Diagnosing Breast Cancer aims to support medical students in enhancing their education regarding diagnosis and counseling. The system facilitates the analysis of biopsy images under a microscope, determination of tumor type, selection of appropriate treatment methods, and identification of disease-related questions. According to the Ministry of Health's annual report in Gaza, there were 7,069 cases of breast cancer between 2009 and 2014, with 1,502 cases reported in 2014. In an era dominated by visual information, where (...) |
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Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, and (...) |
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West Nile virus (WNV) is a mosquito-borne flavivirus that was first identified in 1937 in the West Nile district of Uganda. The virus is now widely distributed throughout the world and is considered a significant public health concern. WNV is primarily transmitted to humans through the bite of infected mosquitoes, with birds serving as the primary reservoir host. Most people infected with WNV will not experience any symptoms, but approximately 1 in 5 will develop a fever, and a smaller percentage (...) |
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Abstract: In modern agriculture, ensuring the quality of crops plays a vital role in enhancing production and minimizing waste. This research focuses on the classification of lemon plants into two categories: good quality and bad quality, using deep learning techniques. We employ convolutional neural networks (CNN) to develop a classification model that can accurately predict plant quality based on images. Through a structured pipeline involving data collection, preprocessing, model design, and evaluation, we demonstrate the effectiveness of CNNs in performing quality (...) |
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