AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson’s disease for the development of neuronal fingerprints using artificial... by Martijn Beudel, Rick Schuurman, Rob M A de Bie, Deborah Hubers, Mariëlle J Stam, Martijn G J de Neeling, Bart J Keulen, Arthur W G Buijink, Bernadette C M van Wijk

“…However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current application uses continuous high-frequency stimulation at a constant intensity, which may reduce efficacy and cause side effects. …”
Get full text

AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality: an AI-CVD study within the Multi-Et... by Ning Ma, Rozemarijn Vliegenthart, Matthew J Budoff, Khurram Nasir, Javier J Zulueta, Jagat Narula, Daniel Levy, Wenjun Fan, Kim Williams, David J Maron, Chenyu Zhang, Prediman K Shah, Zahi Fayad, Morteza Naghavi, Kyle Atlas, Anthony Reeves, Jakob Wasserthal, Thomas Atlas, Claudia I. Henschke, David F. Yankelevitz, Andrea D Branch, Rowena Yip, Sion K Roy, Sabee Molloi, Michael V McConnell, Ioannis Kakadiaris, George Abela, Nathan D. Wong

“…Coronary artery calcium (CAC) scans contain more information than currently reported. We previously reported new artificial intelligence (AI) algorithms applied to CAC scans for opportunistic measurement of bone mineral density, cardiac chamber volumes, left ventricular mass, and other imaging biomarkers collectively referred to as AI-cardiovascular disease (CVD). …”
Get full text

Exploring the best fit: A comparative analysis of AFINN, Textblob, VADER, and Pattern on Arabic reviews for optimal dictionary extraction by Shakeel Ahmad, Sheikh Muhammad Saqib, Asif Hassan Syed, Nashwan Alromema, Ali Kararay

“…However, in the context of the Arabic language, studies predominantly resort to machine learning or deep learning algorithms for sentiment and emotion analysis, often neglecting the utilization of current pre-trained language models. …”
Get full text

InvarNet: Molecular property prediction via rotation invariant graph neural networks by Danyan Chen, Gaoxiang Duan, Dengbao Miao, Xiaoying Zheng, Yongxin Zhu

“…Recently, deep learning methods, particularly Graph Neural Networks (GNNs), have significantly improved efficiency by capturing molecular structures’ invariance under translation, rotation, and permutation. However, current GNN methods require complex data processing, increasing algorithmic complexity. …”
Get full text

Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

“…Abstract Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. …”
Get full text

Comprehensive benchmarking of genome editing quantification methods for plant applications by Zheng Gong, Yan Zhang, Di Xia, Sohye Yoon, Peter Alexander Crisp, José Ramón Botella

“…This is especially important when analyzing heterogeneous populations from transient expression-based approaches used for technology development as well as evaluating of guide RNA (gRNA) performance in planta. However, current studies employ vastly different techniques to quantify genome editing outcomes, limiting the comparability and repeatability of results. …”
Get full text

A Comprehensive Review of Thermal Management Methods and Ideal System Design for Improved Electric Vehicle Battery Pack Performance and Safety by M. Murugan, P. V. Elumalai, KCK Vijayakumar, M. Babu, K. Suresh Kumar, M. Ganesh, Liu Kuang, S. Prabhakar

“…In conclusion, it is a source of material for research scholars, engineers, and policymakers in charge of developing EVs by synthesizing what already exists, highlighting trends at current times, and outlining possible future directions in the continuum of optimizing TMS for the next generation of driving automobile transportation batteries.…”
Get full text

Hyperspectral Imaging for Enhanced Skin Cancer Classification Using Machine Learning by Teng-Li Lin, Arvind Mukundan, Riya Karmakar, Praveen Avala, Wen-Yen Chang, Hsiang-Chen Wang

“…<b>Method:</b> This paper presents a new approach to hyperspectral imaging for enhancing the visualization of skin lesions called the Spectrum-Aided Vision Enhancer (SAVE), which has the ability to convert any RGB image into a narrow-band image (NBI) by combining hyperspectral imaging (HSI) to increase the contrast of the area of the cancerous lesions when compared with the normal tissue, thereby increasing the accuracy of classification. The current study investigates the use of ten different machine learning algorithms for the purpose of classification of AK, BCC, and SK, including convolutional neural network (CNN), random forest (RF), you only look once (YOLO) version 8, support vector machine (SVM), ResNet50, MobileNetV2, Logistic Regression, SVM with stochastic gradient descent (SGD) Classifier, SVM with logarithmic (LOG) Classifier and SVM- Polynomial Classifier, in assessing the capability of the system to differentiate AK from BCC and SK with heightened accuracy. …”
Get full text

Investigating the truncated fractional telegraph equation in engineering: Solitary wave solutions, chaotic and sensitivity analysis by Usman Younas, Jan Muhammad, Muhammad Amin S. Murad, D.K. Almutairi, Aziz Khan, Thabet Abdeljawad

“…The results obtained may enhance the understanding of nonlinear system dynamics and validate current methods, significantly contributing to the fields of nonlinear science and wave phenomena. …”
Get full text

Steganographic model to conceal the secret data in audio files utilizing a fourfold paradigm: Interpolation, multi-layering, optimized sample space, and smoothing by Daffa Tristan Firdaus, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Didacienne Mukanyiligira, Louis Sibomana

“…Moreover, this study recommends that practitioners in steganography with audio data prioritize data concealment algorithms that enhance security over stego audio quality.…”
Get full text

Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review by Natalie S Blencowe, Neil J Smart, George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway

“…This systematic review aims to critically appraise the diagnostic performance of AI algorithms to identify disease from cross-sectional radiological images of the abdominopelvic cavity, to identify current limitations and inform future research.Methods and analysis A systematic search will be conducted on Medline, EMBASE and the Cochrane Central Register of Controlled Trials to identify relevant studies. …”
Get full text

FiSC: A Novel Approach for Fitzpatrick Scale-Based Skin Analyzer&#x2019;s Image Classification by Guillermo Crocker Garcia, Muhammad Numan Khan, Aftab Alam, Josue Obregon, Tamer Abuhmed, Eui-Nam Huh

“…We conducted extensive classification experiments using various Machine Learning algorithms. The results of our cross-validation tests demonstrate a significant improvement in classification accuracy, reaching up to 97%, thereby outperforming state-of-the-art methods without relaxing the accuracy criteria.…”
Get full text

Synergizing Intelligence and Privacy: A Review of Integrating Internet of Things, Large Language Models, and Federated Learning in Advanced Networked Systems by Hongming Yang, Hao Liu, Xin Yuan, Kai Wu, Wei Ni, J. Andrew Zhang, Ren Ping Liu

“…Finally, this review identifies critical open questions and promising future research paths, including ultra-lightweight models, robust algorithms for heterogeneity, machine unlearning, standardized benchmarks, novel FL paradigms, and next-generation security. …”
Get full text

The Emerging Role of Computed Tomography Coronary Angiography in the Left Main Stem Percutaneous Coronary Intervention by Asad Shabbir, Abdelrahman Attia, Nikkole Marie Weber, Mustafa Alhassan, Monika Radike, Conor M Lane, Apurva Bhavana Challa, Malgorzata Wamil

“…This review explores the current applications and future potential of CTCA in guiding LMS PCI, highlighting its role in improving procedural planning, risk assessment, and overall management of this challenging patient population.…”
Get full text

Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…This study aims to evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases and explore their potential impact on clinical practice. …”
Get full text

Multidisciplinary analysis of the prognosis and biological function of NUBPL in gastric cancer by Luqian Liu, Fengyu Zhang, Jiaye Yu, Pingping Dong, Jing Deng, Weiwei Liu, Xinlei Cao, Juanjuan Huang, Xiaoming Lin, Xiangyang Xue

“…BackgroundResearchers are currently concentrating on molecular markers and potential therapeutic targets associated with gastric cancer in light of recent developments in precision medicine and molecular biology. …”
Get full text

A Practical Implementation of Post-Quantum Cryptography for Secure Wireless Communication by Babatunde Ojetunde, Takuya Kurihara, Kazuto Yano, Toshikazu Sakano, Hiroyuki Yokoyama

“…However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without the actual implementation of quantum-resistant cryptography. …”
Get full text

Exploring commercial Global Navigation Satellite System (GNSS) radio occultation (RO) products for planetary boundary layer studies in the Arctic by M. Ganeshan, M. Ganeshan, D. L. Wu, J. A. Santanello, J. Gong, C. Ao, P. Vergados, K. J. Nelson

“…These findings underscore the importance of processing algorithms in achieving accurate lower-atmospheric soundings and Arctic PBLH representation.…”
Get full text

Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…While its development drives global information infrastructure and AI strategies, current models still face challenges such as overfitting, local optima, and inefficiencies in decoding accuracy and computational cost. …”
Get full text

Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Five ML algorithms were developed to identify OME using demographic, clinical, laboratory, and acoustic immittance parameters. …”
Get full text