Pubertal hypothalamic dysfunction: epidemiology, risk factors, features of the clinical course and consequences of pathology in adults by I.S. Lembryk, I.O. Kostitska, O.V. Zhyliak, E.A. Saretsian, D.O. Kulynych, S.A. Shelever, Yu.T. Khruniak

“…A personalized approach to the early diagnosis and management of patients with hypothalamic dysfunction allows to improve therapeutic algorithms and increase the effectiveness of treatment of comorbid pathology in young patients.…”
Get full text

Unraveling the complex genetic landscape of OTOF-related hearing loss: a deep dive into cryptic variants and haplotype phasing by Pei-Hsuan Lin, Cheng-Yu Tsai, Yu-Ting Chiang, Chang-Han Ho, Yue-Sheng Lu, Jacob Shu-Jui Hsu, Yen-Fu Cheng, Shih-Feng Tsai, Chuan-Jen Hsu, Pei-Lung Chen, Chen-Chi Wu

“…The integration of advanced sequencing technologies, predictive algorithms, and functional validation assays will improve the accuracy of molecular diagnosis and inform personalized treatment strategies for individuals with DFNB9. …”
Get full text

Characterization of immune microenvironment associated with medulloblastoma metastasis based on explainable machine learning by Fengmao Zhao, Xiangjun Liu, Jingang Gui, Hailang Sun, Nan Zhang, Yun Peng, Ming Ge, Wei Wang

“…These findings provide a foundation for developing future therapeutic strategies targeting the TME to improve MB patient outcomes.…”
Get full text

MRI radiomics model for predicting tumor immune microenvironment types and efficacy of anti-PD-1/PD-L1 therapy in hepatocellular carcinoma by Rui Zhang, Wei Peng, Yao Wang, Yunping Jiang, Junli Wang, Siying Zhang, Zhi Li, Yushu Shi, Feng Chen, Zhan Feng, Wenbo Xiao

“…Abstract Background To improve the prediction of immune checkpoint inhibitors (ICIs) efficacy in hepatocellular carcinoma (HCC), this study categorized the tumor immune microenvironment (TIME) into two types: immune-activated (IA), characterized by a high CD8 + score and high PD-L1 combined positive score (CPS), and non-immune-activated (NIA), encompassing all other conditions. …”
Get full text

The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target by Yunpeng Zou, Yunpeng Zou, Jianning Kang, Shaopeng Zhu, Xuechen Ren, Zheng Li, Jiayao Niu, Xuanzhe Qin, Hongbo Li, Lu Xiang, Wei Jiang, Jiangbo Zhong, Ying Zhang, Ying Zhang, Kai Zhao

“…High PLEK expression correlated with improved survival and increased infiltration of macrophages, dendritic cells, and CD4+ T cells. …”
Get full text

Heart failure with preserved left ventricular ejection fraction – clinical perspectives by Małgorzata Niemiec, Bartosz Gruchlik, Nicola Dyrek, Jan Niemiec, Bartosz Basiaga, Krzysztof Bednarz, Dorota Piłat, Kinga Czepczor, Maciej Podolski, Katarzyna Mizia-Stec

“…However, newer pharmacological therapies have demonstrated benefits in reducing hospitalizations and improving cardiovascular outcomes. Prognosis in HFpEF remains poor, with a 5-year mortality rate of approximately 75%. …”
Get full text

Early diagnosis of lung cancer using a sensor gas analysis complex: case report by E. O. Rodionov, D. E. Kulbakin, D. V. Podolko, E. V. Obkhodskaya, A. V. Obkhodskiy, S. V. Miller, A. A. Mokh, V. I. Sachkov, A. S. Popov, V. I. Chernov

“…Conclusion. Machine learning algorithms are actively used to diagnose socially significant diseases. the platforms being developed based on arrays of chemical sensors with data analysis using a neural network are promising candidates for implementation in screening activities.…”
Get full text

A machine learning model for predicting lymph node positivity in ovarian cancer: development, validation, and clinical application by QingYong Guo, Jinji Wang, Ru Chen, LiPing Hu, Wenqiang You

“…We developed a machine learning model incorporating multiple algorithms, with XGBoost demonstrating superior performance. …”
Get full text

Neurochallenges in smart cities: state-of-the-art, perspectives, and research directions by Begüm Özkaynak, Necati Aras, İrem Daloğlu Çetinkaya, Cem Ersoy, Özlem Durmaz İncel, Mutlu Koca, İrem Nalça, Turgut Tüzün Onay, Sinan Öncü, Berivan Ülger Vatansever, Eda Yücesoy, Can A. Yücesoy

“…., through the intelligent design of public spaces, mobility, and transportation) and (ii) improve resilience and sustainability (e.g., through better disaster management, planning of city logistics, and waste management). …”
Get full text

A deep learning-orchestrated garlic routing architecture for secure telesurgery operations in healthcare 4.0 by Kavit Shah, Nilesh Kumar Jadav, Rajesh Gupta, Sucheta Gupta, Sudeep Tanwar, Joel J.P.C. Rodrigues, Fayez Alqahtani, Amr Tolba

“…A standard sensor dataset is utilized to train different AI algorithms, such as Long Short Term Memory (LSTM) and Gated Recurrent Neural Networks (GRU), for classifying malicious and non-malicious telesurgery data. …”
Get full text

Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…BackgroundEarly diagnosis can significantly improve survival rate of Pancreatic ductal adenocarcinoma (PDAC), but due to the insidious and non-specific early symptoms, most patients are not suitable for surgery when diagnosed. …”
Get full text

Deep learning-based novel ensemble method with best score transferred-adaptive neuro fuzzy inference system for energy consumption prediction by Birce Dağkurs, İsmail Atacak

“…Background Energy consumption predictions for smart homes and cities benefit many from homeowners to energy suppliers, allowing homeowners to understand and manage their future energy consumption, improve energy efficiency, and reduce energy costs. …”
Get full text

Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA by Tong Y, Wen K, Li E, Ai F, Tang P, Wen H, Guo B

“…Future research can explore the potential of incorporating these predictive factors into comprehensive treatment strategies to improve patient prognosis and overall quality of life.Keywords: machine learning, risk prediction, sleep quality, OSA, SHAP…”
Get full text

Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…This work highlights the power of combining miRNA network biology with ML to improve precision oncology diagnostics and supports future development of liquid biopsy-based cancer classification.…”
Get full text

A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–2018 by Wenqiang Wang, Ruiqing Mo, Xingyu Chen, Sijie Yang

“…With the growing availability of large-scale health datasets and advancements in machine learning, there is an opportunity to improve risk stratification. This study aimed to identify key predictors of obesity and develop a machine learning-based predictive model for patients with T2DM using data from the National Health and Nutrition Examination Survey (NHANES).MethodsData from adults with diabetes were extracted from the NHANES 2007–2018 cycles. …”
Get full text

Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. Furthermore, model stacking and average ensemble learning methods were adopted to further improve the generalization performance of the model. …”
Get full text

Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

“…Using appropriate algorithmic techniques, the study expects the model to have a sensitivity of >80% and a positive predicted value of >70%. …”
Get full text

Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study by Jin-Hyun Park, Inyong Jeong, Gang-Jee Ko, Seogsong Jeong, Hwamin Lee

“…Developing a noninvasive and scalable predictive model could enhance accessibility and improve early detection. ObjectiveThis study aimed to develop and validate a predictive model for metabolic syndrome using noninvasive body composition data. …”
Get full text

Using Video Cameras to Assess Physical Activity and Other Well-Being Behaviors in Urban Environments: Feasibility, Reliability, and Participant Reactivity Studies by Jack S Benton, James Evans, Jamie Anderson, David P French

“…This research is a significant first step in demonstrating the potential for camera-based methods to improve natural experimental studies of real-world environmental interventions. …”
Get full text

Exploration of biomarkers for predicting the prognosis of patients with diffuse large B-cell lymphoma by machine-learning analysis by Shifen Wang, Hong Tao, Xingyun Zhao, Siwen Wu, Chunwei Yang, Yuanfei Shi, Zhenshu Xu, Dawei Cui

“…However, the molecular mechanisms that underlie this association have not been clearly elucidated. To improve this situation, it is urgent to explore disease-specific diagnostic biomarkers and mechanisms. …”
Get full text