Development and Validation of a Clinical Risk Model for Predicting Malignancy in Patients with Thyroid Nodules by Shiva Borzouei, Ali Safdari, Erfan Ayubi

“…Generally, there was no difference among the six ML algorithms in terms of prognostic performance; however, the prognostic parameters of GLM and LDA algorithms were higher than the others. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…The prevailing development of quantum computing and machine learning (ML) technologies may bring practical improvement to the performance of CHD diagnosis. …”
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A genetic association study of serum acute-phase C-reactive protein levels in rheumatoid arthritis: implications for clinical interpretation. by Benjamin Rhodes, Marilyn E Merriman, Andrew Harrison, Michael J Nissen, Malcolm Smith, Lisa Stamp, Sophia Steer, Tony R Merriman, Timothy J Vyse

“…CRP is increasingly being incorporated into clinical algorithms to compare disease activity between patients and to predict future clinical events: our findings impact on the use of these algorithms. …”
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Machine learning models for prediction of lymph node metastasis in patients with gastric cancer: a Chinese single-centre study with external validation in an Asian American populat... by Qian Li, Yuan Tian, Wei Peng, Shangcheng Yan, Weiran Yang, Zhuan Du, Ming Cheng, Renwei Chen, Qiankun Shao, Mengchao Sheng, Yongyou Wu

“…Objective To develop and validate machine learning (ML)-based models to predict lymph node metastasis (LNM) in patients with gastric cancer (GC).Design Retrospective cohort study.Setting Second Affiliated Hospital of Soochow University.Participants A total of 500 inpatients from the Second Affiliated Hospital of Soochow University, collected retrospectively between 1 April 2018 and 31 March 2023, were used as the training set, while 824 Asian patients from the Surveillance, Epidemiology and End Results database comprised the external validation set.Main outcome measures Prediction models were developed using multiple ML algorithms, including logistic regression, support vector machine, k-nearest neighbours, naive Bayes, decision tree (DT), gradient boosting DT, random forest and artificial neural network (ANN). …”
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The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“…This allows for more accurate and timely diagnoses, as AI algorithms can detect subtle patterns and anomalies that may not be visible to human observers. …”
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Enhancing Detection of Multi-Frequency-Modulated SSVEP Using Phase Difference Constrained Canonical Correlation Analysis by Chi Man Wong, Ze Wang, Boyu Wang, Agostinho Rosa, Tzyy-Ping Jung, Feng Wan

“…However, the existing calibration-free recognition algorithms based on the traditional canonical correlation analysis (CCA) cannot provide the merited performance. …”
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Enhanced MCDM Based on the TOPSIS Technique and Aggregation Operators Under the Bipolar pqr-Spherical Fuzzy Environment: An Application in Firm Supplier Selection by Zanyar A. Ameen, Hariwan Fadhil M. Salih, Amlak I. Alajlan, Ramadhan A. Mohammed, Baravan A. Asaad

“…Moreover, a numerical example is provided in order to ensure that the presented model is applicable. By using the two algorithms, a comparative analysis of the proposed method with other existing ones is given in order to verify the feasibility of the suggested decision-making procedure.…”
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Guideline Directed Anticoagulant Treatment and Dosing in a Contemporary Atrial Fibrillation Cohort: Analysis of the TRANSECT-AF Program by Cole Clifford, MD, Shaun G. Goodman, MD, MSc, Mary K. Tan, MSc, Jean Gregoire, MD, Jeffrey Habert, MD, Anil Gupta, MD, Walter Chow, MD, Shahin Jaffer, MD, MHSc, Sandeep G. Aggarwal, MD, Michael Heffernan, MD, Robert Maranda, MD, Kevin Saunders, MD, Andrew T. Yan, MD, Sandeep Aggarwal, Grant Campbell, Tony Ford, Allan Kelly, Michael Kroetsch, Jean-Pierre Leung, Indra Patel, Qaiser Rizvi, Matthew Wong, Andrew Wong, Jessica Chan, Kenneth Cho, Walter Chow, Daniel Ezekiel, Shahin Jaffer, Al Karmali, Parbhoobhai Lakhoo, Dante Manyari, Tun Zan Maung, Laura Ozolins, Ameet Parikh, Walter Salmaniw, Masoud Shahrokhi, Alex She, Kanwarinder Sidhu, Raymond Simkus, Felix Tam, Richard Van Gend, Jeffrey T. Wang, Jonathan Wiltshire, Felix Yang, David Yoon, Daljit Gill, David Haligowski, Yatish Kotecha, Abraham C. Mare, Pravinsagar Mehta, Sunilkumar Patel, Kevin Saunders, Gilbert Blanchard, Steve Kenney, Oluwasyo Olatunde, Gary Rideout, William Booth, Adam Clarke, Malcolm Lawrence Macneil, Vineeta Ahooja, Lina Alkasm, Edgard Arcia-Bravo, Ogunroti Ayibiowu, Basel Bari, Parvinder Bath, Rani Beharry, Rajendra Beharry, Ira Bernstein, Mukesh Bhargava, Leon Bhatia, Harry Birman, Brent Bukovy, Craig Campagna, Claudius Che, Richard Chen, Michael Cheng, Grace Chua, Kim Connelly, Michael Csanadi, Maynard Luterman, Gregory Curnew, Shyamali Damboragama, Sampa Das, Selwyn De Souza, Nicole Desmarais, Debbie Dyke, Fadia El Boreky, Sameh Fikry, Ken Florence, Omayma Fouda, Melody Fox, Gissou Ghadirian, Magdy Girgis, Steven Grossman, Anil Gupta, Nassoh Hafez, Adnan Hameed, Brian Hartford, Michael Heffernan, Terry Holman, Brendan Hughes, Harry Jim, David Josephson, Amjad Junaid, Bharat Kalra, Nikolay Kaplan, Saleem Kassam, Aubrey Kassirer, Tammy Kauffman-Schenker, Hashmat Khan, Natan Khotianov, Myung-Gi Kim, Kinga Koprowicz, Joseph Kozak, Naresh Kumar, Adel Kyrollos, Andy Lam, David Lam, Howard Lamb, Ming Jarm Lau, Doris Lee, Christina Lo, Giridhar Logsetty, Victoria Malevich, Robert Maranda, Rohit Nagpal, Farah Nasser-Sharif, Ken H. Ng, Parminder Nizran, Luis Noronha, Huma N. Numair, Paul O. Oladipo, Chris Overgaard, Derek Papastergiou, Fred Parker, Keyvan Pazuki, Murray Pearce, Sean Peterson, Mohammed Rahman, Felice Emilio Raimondo, Tim Remillard, Gerald Rockman, Howard Rudner, Roland Sabbagh, Ashraf Salib, Raymond Sawkiw, Earl Schwartz, Shiraz Shariff, Ivan Shcherbatykh, Mike Chungming Shih, Sewa Ram Singal, Sol Stern, Ravi Tahiliani, Manoj Tahiliani, Arawn Therrien, Bill Tillmann, Camelia Trambitas, Andrew Trevor, Jeff Tschirhart, Shera Vania, Elisa Venier, Vinod Verma, George Vertes, David Walley, Hany William, Amy Wong, Kevin Yoong, Derek Yung, Ines Zepic, Dean Zizzo, Harold Molyneaux, Paul Phelan, Martin Albert, Jean Champagne, Jacques Desroches, Danielle Dion, Richard Dumouchel, Carl Fournier, Mario Labbe, Germain Savard, Dan Dattani, Cecil Hammond, Andrea Lavoie, Omar Sultan

“…Our analysis describes predictors of guideline discordant anticoagulation and DOAC dosing that may be used to identify target populations for future quality improvement initiatives in AF thromboprophylaxis. …”
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Optimizing Inotropic Infusion With Cluster Specific AI Decision Models and Digital Twins by Vidya S Nair, G. D. Heshan Niranga, Aryalakshmi C.S, Dipu T. Sathyapalan, Thushara Madathil, Rahul Krishnan Pathinarupothi

“…Conventional feedback controllers, including fuzzy logic controllers (FLC), struggle to adapt to complex BP variations due to fixed algorithms and intracohort variability in drug responses. …”
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COMBINED ANALYSIS OF LINKAGE AND WHOLE EXOME SEQUENCING REVEALS CIC AS A CANDIDATE GENE FOR ISOLATED DYSTONIA by Barış Salman, Emrah Yücesan, Bedia Samancı, Başar Bilgiç, Haşmet Ayhan Hanağası, İbrahim Hakan Gürvit, Uğur Özbek, Sibel Aylin Uğur İşeri

“…An in-house pipeline compiled for WES analysis along with in-depth in silico prediction algorithms were used to assess the associated data produced in this study. …”
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Artificial Intelligence (AI) and Drug-Induced and Idiosyncratic Cytopenia: The Role of AI in Prevention, Prediction, and Patient Participation by Emmanuel Andrès, Amir El Hassani Hajjam, Frédéric Maloisel, Maria Belén Alonso-Ortiz, Manuel Méndez-Bailón, Thierry Lavigne, Xavier Jannot, Noel Lorenzo-Villalba

“…With its ability to process vast amounts of clinical, genomic, and pharmacovigilance data, AI can identify patterns and risk factors that may be missed by traditional methods. Machine learning algorithms can refine predictive models, enabling earlier detection and more accurate risk assessments. …”
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Limited-Preemption EDF Scheduling for Multi-Phase Secure Tasks by Standaert, Benjamin, Raadia, Fatima, Sudvarg, Marion, Baruah, Sanjoy, Chantem, Thidapat, Fisher, Nathan, Gill, Christopher

“…As these systems become more complex and inter-connected, some parts may need to be secured to prevent unauthorized access, or isolated to ensure correctness. …”
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Prognostic and Diagnostic Value of Spontaneous Tumor-Related Antibodies by Sebastian Kobold, Tim Luetkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic

“…Larger prospective trials should be initiated to identify sets of tumor-associated autoantibodies suited for the use in diagnostic algorithms for cancer detection and followup.…”
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Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study by Urszula Bialonczyk, Malgorzata Debowska, Lu Dai, Abdul Rashid Qureshi, Leon Bobrowski, Magnus Soderberg, Bengt Lindholm, Peter Stenvinkel, Tomasz Lukaszuk, Jan Poleszczuk

“…Abstract Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overlooked. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…However, implementing these technologies may pose several challenges to the B5G network. …”
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Prediction of hearing aid cognitive outcomes in age-related hearing loss by Patrice Voss, Zaida Escila Martinez-Moreno, Francois Prévost, Anthony Zeitouni, Alejandro Lopez Valdes, Alejandro Lopez Valdes, Alejandro Lopez Valdes, Alejandro Lopez Valdes, Etienne de Villers-Sidani

“…Although the phenomena underlying cognitive decline and dementia are complex, there is growing evidence suggesting that degraded sensory inputs caused by age-related hearing loss may play a central role in accelerating cognitive decline in older individuals. …”
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Castleman Disease: Insights from a Case Series and Literature Review by Jerin James, Sanudev Sadanandan Vadakke Puthiyottil, Johan George, Arathi Edayattil, Vivek Mathew James, Swapna Dominic, Supriya N. K.

“…By integrating clinical experiences with literature, it advocates for refined diagnostic criteria and context-specific therapeutic algorithms, urging further research to address gaps in managing this complex disease.…”
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A Specific Time Lag Regulation of Soil Moisture Across Layers on Soil Salinization in the Northeast Tibetan Plateau Agroecosystem by Di Wei, Ziqi Zhang, Lin Yan, Jia Yu, Yun Zhang, Bo Wang

“…Moreover, soil water and salt also have a time lag effect compared with instant responses, meaning that the soil salinization caused by deep soil moisture may require longer transport times. As the potential driving factors, an increase in soil organic carbon and runoff is beneficial for alleviating salinization while abundant runoff also promotes soil humidification. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…In contrast to conventional inspection techniques, UAV-based photography provides continuous, real-time surveillance, facilitating the rapid detection of potential defects such as cell malfunctions, fractures, shading, and string failures, which may result in substantial financial losses. The choice to prioritize thermal and visual imaging above mathematical modeling or optimization algorithms arises from the necessity of delivering practical, scalable inspection solutions that can be readily implemented in the field. …”
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Analysis of Distributed Dynamic Loads Induced by the Own Mass of Manipulator Links and Their Visualization on Interactive 3D Computer Models by Muratulla Utenov, Tarek Sobh, Yerbol Temirbekov, Saltanat Zhilkibayeva, Sarosh Patel, Dauren Baltabay, Zhadyra Zhumasheva

“…This study proposes an approach to 3D modeling of spatial manipulators in the Maple 2023 software environment. Algorithms and program codes have been developed to create computer 3D models of manipulators controlled by generalized coordinates. …”
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