A model-based approach to detection of the circulating melanoma cells from the photoacoustic cytometry data by Yurii M. Ishbulatov, Viktoriia V. Skazkina, Anatoly S. Karavaev, Olga A. Inozemtseva, Daniil N. Bratashov, Arkady S. Abdurashitov, Oleg V. Grishin, Alexey N. Hramkov, Vladimir P. Zharov

“…However, current techniques of cancer diagnostics are not sensitive enough to be reliable during the early stages. …”
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A Quest for Innovation Drivers with Autometrics: Do These Differ Before and After the COVID-19 Pandemic for European Economies? by Jorge Marques, Carlos Santos, Maria Alberta Oliveira

“…The final models provided by Autometrics allow for valid inference on retained innovation drivers since they have passed a plethora of diagnostic tests, ensuring congruency. The attractiveness of the research system is the most impactful driver on the index in both years but other drivers indeed differ. …”
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Directivity enhancement of microstrip antennas for high-resolution brain tumor imaging using characteristic modes theory and the confocal microwave image reconstruction algorithm by Mouad El Moudden, Badiaa Ait Ahmed, Ibtisam Amdaouch, Mohamed Zied Chaari, Juan Ruiz-Alzola, Otman Aghzout

“…This advanced system is carefully designed to accurately locate and characterize brain tumors, enhancing diagnostic precision. The confocal imaging algorithm demonstrates that the dominant mode with high directivity radiation produces high-resolution images that significantly improve tumor detection and diagnosis.…”
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Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10‐Year Retrospective Study by Ameer A. Megahed, Y. Reddy Bommineni, Michael Short, João H. J. Bittar

“…Objectives To compare six different supervised machine‐learning (SML) algorithms used to identify the most important risk factors for predicting BLV seropositivity in beef cattle in Florida. …”
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Potential Metabolic Markers in the Tongue Coating of Chronic Gastritis Patients for Distinguishing Between Cold Dampness Pattern and Damp Heat Pattern in Traditional Chinese Medici... by Yuan S, Zhang R, Zhu Z, Zhou X, Zhang H, Li X, Hao Y

“…Tongue coating differences are key diagnostic markers, yet molecular-level analyses are lacking. …”
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Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen by Robert Gaudin, Wolfram Otto, Iman Ghanad, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…This study aims to develop a robust artificial intelligence (AI) application for accurate osteoporosis identification in PRs, contributing to early and reliable diagnostics. A total of 250 PRs from three groups (A: osteoporosis group, B: non-osteoporosis group matching A in age and gender, C: non-osteoporosis group differing from A in age and gender) were cropped to the mental foramen region. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…The SA-CS algorithm extends SA by preventing entrapment in local minimum and enhancing global exploration. …”
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Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm by Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy

“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. This technique is expected to be further developed and applied in different tasks of computer aided diagnosis of malignant lymphoma in particular the tasks with requirements for explainable artificial intelligence.…”
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Modern Methods for Diagnosing Faults in Rotor Systems: A Comprehensive Review and Prospects for AI-Based Expert Systems by Oleksandr Roshchupkin, Ivan Pavlenko

“…Some techniques like the vibration signal analysis method, spectral analysis, thermography, ultrasound diagnosis, and machine learning algorithms for predicting failure are of particular interest among them. …”
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Research on Rolling Bearing Fault Diagnosis Method Based on MPE and Multi-Strategy Improved Sparrow Search Algorithm Under Local Mean Decomposition by Haodong Chi, Huiyuan Chen

“…Second, to overcome the limited capability of traditional time-frequency features in representing complex fault patterns, MPE is introduced to construct a multi-scale complexity feature vector, effectively capturing the scale-dependent differences in the dynamic behavior of signals. Furthermore, considering the instability of classification caused by the empirical setting of hidden layer nodes in the extreme learning machine (ELM), a multi-strategy improved sparrow search algorithm is proposed to optimize ELM parameters. …”
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Directed carbapenemase testing is no longer just for Enterobacterales: cost, labor, and workflow assessment of expanding carbapenemase testing to carbapenem-resistant P. aeruginosa by Christian M. Gill, Poonam Rajkotia, Amity L. Roberts, Fred C. Tenover, David P. Nicolau

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The Mobile Complex of Chemical Control as the Basis of Technical Equipment of the Mobile Diagnostic Group of the 33 Central Scientific Research Test Institute of the Ministry of De... by V. A. Inozemtsev, A. K. Zhokhov, A. Yu. Boyko, A. S. Samorodov, A. V. Zhidyaev, A. A. Braginets

“…The special mobile diagnostic group (MDG) is formed in the Federal State Budgetary Establishment «33 Central Scientific Research Test Institute» of the Ministry of Defenсe of the Russian Federation (hereinafter referred to as the institute) to perform tasks related to the radiation and chemical (RCh) control of different objects, to ensure RCh safety and security of mass events, as well as to perform special tasks of RCh examination of samples of all kinds. …”
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Classification Analytics for Wind Turbine Blade Faults: Integrated Signal Analysis and Machine Learning Approach by Waqar Ali, Idriss El-Thalji, Knut Erik Teigen Giljarhus, Andreas Delimitis

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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis by Termeh Sarrafan Sadeghi, Seyed AmirHossein Ourang, Fatemeh Sohrabniya, Soroush Sadr, Parnian Shobeiri, Saeed Reza Motamedian

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The Value of Clinical Decision Support in Healthcare: A Focus on Screening and Early Detection by Hendrik Schäfer, Nesrine Lajmi, Paolo Valente, Alessandro Pedrioli, Daniel Cigoianu, Bernhard Hoehne, Michaela Schenk, Chaohui Guo, Ruby Singhrao, Deniz Gmuer, Rezwan Ahmed, Maximilian Silchmüller, Okan Ekinci

“…This review aims to (i) describe the purpose and mechanisms of CDS systems, (ii) discuss different entities of algorithms, (iii) highlight quality features, and (iv) discuss challenges and limitations of CDS in clinical practice. …”
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Evaluating the accuracy of artificial intelligence-powered chest X-ray diagnosis for paediatric pulmonary tuberculosis (EVAL-PAEDTBAID): Study protocol for a multi-centre diagnosti... by Heather J Zar, Savvas Andronikou, Lesley Workman, Tehmina Mustafa, Dennis Robert, Brekhna Aurangzeb, Cynthia Baard, Abid Ali Qureshi, Aneela Shaheen, Atiqa Ambreen, David McFarlane, Humera Javed, Iqbal Bano, Justy Antony Chiramal, Tanyia Pillay, Zoe Franckling-Smith

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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

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Overall survival in colon cancer patients with different levels of circulating tumor cells and feasibility of enhancing its prognostic value by O. I. Kit, E. Y. Zlatnik, I. A. Novikova, E. P. Ulianova, A. A. Demidova, E. N. Kolesnikov, Yu. A. Gevorkyan, N. V. Soldatkina, A. V. Snezhko

“…OS was studied in patients with different CTC levels, cumulative OS was calculated by Kaplan–Meier`s method. prognostic algorithm was designed by logistic regression analysis and cox proportional hazards model. …”
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A robust tuned EfficientNet-B2 using dynamic learning for predicting different grades of brain cancer by A. A. Abd El-Aziz, Mohammed Elmogy, Sameh Abd El-Ghany

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A Case Series of Different Cutaneous Adverse Drug Reactions Attending the Dermatology Clinic of a Tertiary Care Center by Debalina Kanjilal, Suhena Sarkar, Abanti Saha, Birupaksha Biswas, Soutrik Roy

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