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Discover Artificial Intelligence
Scopus
ISSN 2731-0809 · Springer · 1.896 artikel di indeks
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Artikel Jurnal
Systematic review of emerging artificial intelligence research in glioma diagnosis and therapy
Abstract Brain tumor management is one of the most challenging domains in neurosurgery, where timely diagnosis and intervention are critical, yet differentiating between diagnoses often presents difficulties. Despite advances, treatment options, especially for malignant tumors, have largely…
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Artikel Jurnal
An integrated model for early breast cancer prediction using microcalcifications and patient risk factors
Abstract Microcalcifications on mammograms are one of the earliest radiographic indicators of breast cancer and patient outcomes are significantly improved by early detection. The recent advances in deep learning have improved mammography interpretation to overlook the crucial context provided by…
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Artikel Jurnal
Hybrid cryptographic and AI frameworks for cheat detection in online games
Abstract The exponential growth of multiplayer gaming has led to the formation of an arms race between anticheat and cheat developers, which has been increasing in pace at an exponential rate, creating a need for the implementation of robust anti-cheat mechanisms for maintaining fair play. While…
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Artikel Jurnal
Unveiling the intellectual landscape of artificial intelligence and consumer behavior
Abstract The rapid integration of artificial intelligence (AI) in marketing has fundamentally transformed consumer behavior research. This study presents a comprehensive bibliometric analysis of the academic literature on AI and consumer behavior published between 2015 and 2025. Drawing on 56…
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Artikel Jurnal
Deep transfer learning and contour-based morphological analysis for detection of eye-hypertensive diseases from fundus images
Abstract Hypertensive eye disease produces subtle retinal changes that are often challenging for automated systems to recognize reliably. This paper proposes a hybrid diagnostic framework that combines contour-based morphological descriptors with deep transfer learning to classify hypertensive…
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Artikel Jurnal
Investigation of machine learning methods for predicting surgical parameters in strabismus surgery
Abstract Purpose To minimize the variability of surgical outcomes in strabismus surgery we evaluated machine learning models that predict the dosage for surgical correction of horizontal non-paretic strabismus, based on preoperative features and tried to determine feature importance with…
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Artikel Jurnal
Hybrid stacking of Squeeze Net features and ML models for accurate Alzheimer’s diagnosis
Abstract Alzheimer’s Disease (AD), a leading cause of dementia, demands early diagnosis for effective intervention. This study introduces a hybrid framework combining SqueezeNet—a lightweight convolutional neural network—with ensemble stacking of machine learning (ML) models to enhance AD detection…
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Artikel Jurnal
Homomorphic approximation of non-linear activation functions using the CKKS cryptosystem of the OpenFHE library
Abstract Homomorphic computing can be viewed as the holy grail of encryption, as it allows evaluating computations on encrypted data. This enables perfect privacy for cloud applications, as a cloud provider handling user data never gets to see the data it is performing calculations on…
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Artikel Jurnal
Challenges for generative AI in legal reasoning
Abstract Large Language Models (LLMs) are being integrated into professional domains, yet their limitations in such high-stakes fields as law remain poorly understood. In response, this paper introduces examples of critical challenges to the functioning of generative and other forms of artificial…
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Artikel Jurnal
Enhancing face mask detection performance using stacked neural ensembles in mask fusion
Abstract The COVID-19 pandemic highlighted the importance of face mask usage in public health safety, giving way to automated face mask detection, especially for real-time surveillance. This paper presents a comprehensive approach for binary face mask classification using deep learning techniques…
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Artikel Jurnal
Comparative evaluation of large language models in generating clinical insights for HIV associated oral Kaposi sarcoma
Abstract Objectives The objective of this study was to quantitatively evaluate and compare the performance of three advanced generative AI models, ChatGPT (v4.0), Gemini (v2.0 advanced), and Meta AI (Llama 3.2) in providing accurate information of AIDS-associated Oral Kaposi Sarcoma (OKS). Methods…
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Artikel Jurnal
Quantum-like cognition and AI toward the convergence of natural and artificial intelligence
Abstract The gap between natural and artificial intelligence is often discussed in terms of creativity, contextual adaptability, and non-algorithmic decision-making capacities where human cognition appears fundamentally different from current AI systems. This paper argues that developing quantum…
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Artikel Jurnal
Prediction of maize yield in Uganda using CNN-LSTM architecture on a multimodal climate and remote sensing dataset
Abstract Maize is a staple crop in Uganda, underpinning both food security and rural livelihoods. Accurate forecasting of maize yields is therefore crucial for guiding agricultural planning, resource allocation, and policy design. Yet traditional statistical methods are often limited by low…
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Artikel Jurnal
LLM-guided deep reinforcement learning with contrastive safety regularization for autonomous driving
Abstract Deep Reinforcement Learning has shown immense potential in autonomous driving decision-making; however, its application in safety–critical scenarios such as highways still faces significant challenges in data efficiency and safety performance. To address this, this paper proposes an…
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Artikel Jurnal
Reinforcement learning-driven optimization of incentive-based demand response in distribution network with optimal placement of DG
Abstract Demand response (DR) is a key strategy for strengthening the economic efficiency, planning and operational stability of microgrids. This paper proposes an incentive-based DR program implemented through agent-based reinforcement learning, designed to optimize the profit of both the…
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Artikel Jurnal
Exploring potential of large language models for automated essay scoring in education
Abstract The assessment of open-ended written work is of vital importance to the student learning experience. Conventional essay grading methods heavily depend on expert manual assessment, making them susceptible to errors due to fatigue, bias, and subjectivity. To address this, recent research has…
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Artikel Jurnal
The influence of affective AI literacy on student satisfaction in higher education
Abstract This study explores the impact of affective AI literacy on student satisfaction in Pakistan’s evolving higher education sector, which is placing greater emphasis on sustainable education and market-relevant skills. Technology Acceptance Model together with the Cognitive-Affective Theory of…
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