Identifying time patterns in Huntington’s disease trajectories using dynamic time warping-based clustering on multi-modal data by Alexia Giannoula, Audrey E. De Paepe, Ferran Sanz, Laura I. Furlong, Estela Camara

“…Building on an earlier methodology, a new dimension of time-varying clinical and imaging features is incorporated, through an adapted cost-minimization algorithm for clustering on different, possibly overlapping, feature subsets. …”
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Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis. by Swati Jha, Nazir Ismail, David Clark, James J Lewis, Shaheed Omar, Andries Dreyer, Violet Chihota, Gavin Churchyard, David W Dowdy

“…The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain.…”
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Interdisciplinary model of patient care for groups at risk for malignant tumors of the skin by M. A. Ufimtseva, A. S. Shubina, V. V. Petkau, N. L. Struin, D. E. Emel'janov, E. A. Levchenko

“…Neoplasia data refer to tumors of apparent localization, therefore, they are found in the clinical practice of doctors of different profiles. The duration of the diagnostic period, as well as the prognosis, depends on the coordinated work of specialists.Aim. …”
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Estimating individuals' genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data. by Christopher M Pooley, Glenn Marion, Stephen C Bishop, Richard I Bailey, Andrea B Doeschl-Wilson

“…SIRE implements a flexible Bayesian algorithm which accommodates a wide range of disease surveillance data comprising any combination of recorded individual infection and/or recovery times, or disease diagnostic test results. …”
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Multimodal Classification of Alzheimer’s Disease Using Longitudinal Data Analysis and Hypergraph Regularized Multi-Task Feature Selection by Shuaiqun Wang, Huan Zhang, Wei Kong

“…Therefore, in this paper, we propose a multi-task feature selection algorithm for Alzheimer’s disease classification based on longitudinal imaging and hypergraphs (THM2TFS). …”
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Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…Results One of our unique discoveries is that, using our datasets, we verified that our proposed algorithm, DMTCNN, could appropriately categorize dissimilar brain disorders. …”
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Identifying key genes involved in HBV-related hepatocellular carcinoma: diagnose, prognosis, interaction and immune analysis by Yan Li, Sa-Sa Liu, Hua-Rong Jing, Hong-Wei Qian, Rui-Cheng Li

“…Survival analysis and receiver operator characteristic (ROC) curve were used to explore the prognostic and diagnostic value of key genes. Immune infiltration analysis were performed by CIBERSORT algorithm. …”
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Modern aspects of diagnosis and treatment of patients with spontaneous coronary artery dissection by Sh. Sh. Zainobidinov, D. A. Khelimsky, A. A. Baranov, A. G. Badoyan, O. V. Krestyaninov

“…The angiographic classification of SCAD, the diagnostic algorithm and the choice of optimal treatment depending on clinical manifestations are also described.…”
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Hepatopulmonary syndrome by V. T. Ivashkin, M. A. Morozova, M. V. Mayevskaya

“…Today investigators' views of the causes and pathogenesis of dilated pulmonary vessels and abnormal blood gas composition differ in HPS. To date, its clear diagnostic algorithm and treatment policy for patients with HPS have not been elaborated.…”
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Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. …”
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AFSA-FastICA-CEEMD Rolling Bearing Fault Diagnosis Method Based on Acoustic Signals by Jin Yan, Fubing Zhou, Xu Zhu, Dapeng Zhang

“…Acoustic signal is a commonly used method in the field of mechanical fault diagnosis, but an overlapping phenomenon occurs very easily, which affects the diagnostic accuracy. Therefore, effective blind source separation and noise reduction of the acoustic signals generated between different devices is the key to bearing fault diagnosis using acoustic signals. …”
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The value of a combined model based on ultra-radiomics and multi-modal ultrasound in the benign-malignant differentiation of C-TIRADS 4A thyroid nodules: a prospective multicenter... by Shuai Cui, Qifan Liu, Hailong Wang, Husha Li, Wei Li, Chenlong Li, Leilei Bi, Yang Mu, Wenjing Guo, Jundong Yao, Zhoulong Zhang

“…DeLong’s test showed that the combined model performed best in the training set, and in the test set, the combined model outperformed the multimodal ultrasound model but showed no significant difference compared to the radiomics model. DCA indicated that the combined model achieved higher net benefits within a specific threshold probability range (0.15-0.90).ConclusionThe combined model exhibits robust diagnostic capability in distinguishing benign from malignant thyroid nodules classified as C-TIRADS 4A.…”
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Comment on “Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation” by Hinpetch Daungsupawong, Viroj Wiwanitkit

“…By incorporating advanced imaging techniques and machine learning algorithms, researchers can improve the accuracy and efficiency of diagnostic processes. …”
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Clinical Characterization of Patients with Syncope of Unclear Cause Using Unsupervised Machine-Learning Tools: A Pilot Study by María-José Muñoz-Martínez, Manuel Casal-Guisande, María Torres-Durán, Bernardo Sopeña, Alberto Fernández-Villar

“…Syncope of unclear cause (SUC) presents a significant diagnostic challenge, with a considerable proportion of patients remaining without a definitive diagnosis despite comprehensive clinical evaluation. …”
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The Author's Reply by Mohamad Reza Golzar Feshalami, Mehraban Shahi, Nasrin Davari Dolatabadi

“…The commenter rightly points out the need for a more detailed exploration of specific types of odontogenic tumors that present significant diagnostic challenges. While our article aimed to provide a broad overview of the diagnostic complexities across various tumor types, we acknowledge that a deeper dive into individual tumor characteristics and diagnostic hurdles would have enriched the discussion.Moving forward, we recognize the importance of focusing research efforts on developing AI algorithms that can effectively differentiate between different types of odontogenic tumors based on their unique clinical and radiographic features. …”
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Constipation in Children: Assisting Paediatricians by I. N. Zakharova, N. G Sugyan, I. D. Maykova, I. V. Berezhnaya, I. М. Kolobashkina

“…The article describes risk factors for juvenile constipation and an algorithm for differential diagnosis of chronic constipation and Hirschprung’s disease. …”
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Early postoperative seizures in liver and kidney recipients by O. M. Tsirulnikova, A. V. Syrkina, I. A. Miloserdov, I. E. Pashkova, S. Yu. Oleshkevich, I. B. Komarova

“…Due to the multiple causes of ACS, there are differences in treatment tactics. Further accumulation and generalization of ACS outcome data will help in creating a convenient algorithm for rapid identification of the cause and the most effective treatment tactics.…”
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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

“…<b>Methods</b>: This paper provides a comprehensive review of key studies documenting the use of AI in venous pathology diagnostics, with different electronic databases being searched, including MEDLINE/Pub Med, Web of Science, Scopus, Embase, ResearchGate, and Google Scholar. …”
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AI-based body composition analysis of CT data has the potential to predict disease course in patients with multiple myeloma by Franz Wegner, Malte Maria Sieren, Hanna Grasshoff, Lennart Berkel, Christoph Rowold, Marcel Philipp Röttgerding, Soleiman Khalil, Sam Mogadas, Felix Nensa, René Hosch, Gabriela Riemekasten, Anna Franziska Hamm, Nikolas von Bubnoff, Jörg Barkhausen, Roman Kloeckner, Cyrus Khandanpour, Theo Leitner

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Antibacterial therapy of pyogenic liver abscesses by V. V. Novak, V. O. Belinska

“…The main group consisted of 44 patients operated on minimally invasive technologies based on modern diagnostic methods. They received a comprehensive conservative therapy, which took into account antibacterial treatment according to the developed algorithm. …”
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