Risk factors and prediction model of breast cancer-related lymphoedema in a Chinese cancer centre: a prospective cohort study protocol by Yue Wang, Xin Li, Ying Wang, Hongmei Zhao, Qian Lu, Yujie Zhou, Liyuan Zhang, Aomei Shen, Jingru Bian, Wanmin Qiang, Jingming Ye, Hongmeng Zhao, Yubei Huang, Zhongning Zhang, Peipei Wu

“…However, the reported incidence of lymphoedema varies, and its risk factors remain underexplored. Currently, a well-established risk prediction model is still lacking. …”
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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

“…Background. Currently, low-dose computed tomography (LDCT) is the only screening test that reduces the risk of death from lung cancer. …”
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Biologging intelligent Platform (BiP): an integrated and standardized platform for sharing, visualizing, and analyzing biologging data by Katsufumi Sato, Shinichi Watanabe, Takuji Noda, Takuya Koizumi, Ken Yoda, Yuuki Y. Watanabe, Kentaro Q. Sakamoto, Teijiro Isokawa, Makoto A. Yoshida, Kagari Aoki, Akinori Takahashi, Takashi Iwata, Hideaki Nishizawa, Takuya Maekawa, Ryo Kawabe, Yutaka Watanuki

“…Algorithms published in some previous studies are integrated into the OLAP which can estimate the environmental and behavioral parameters. …”
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Disease activity and treatment response in early rheumatoid arthritis: an exploratory metabolomic profiling in the NORD-STAR cohort by Tahzeeb Fatima, Yuan Zhang, Georgios K. Vasileiadis, Araz Rawshani, Ronald van Vollenhoven, Jon Lampa, Bjorn Gudbjornsson, Espen A. Haavardsholm, Dan Nordström, Gerdur Gröndal, Kim Hørslev-Petersen, Kristina Lend, Marte S. Heiberg, Merete Lund Hetland, Michael Nurmohamed, Mikkel Østergaard, Till Uhlig, Tuulikki Sokka-Isler, Anna Rudin, Cristina Maglio

“…Identification of biomarkers linked to clinical remission in RA is currently a challenge. Metabolomics may help to identify such biomarkers as it allows for a comprehensive exploration of disease-related variations that extends beyond the genome and proteome. …”
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Challenges and inequalities in the management of financing the tasks of local government units: a critical analysis by Arkadiusz Ciach

“…As a result of underestimating the educational subsidy, are local government units forced to redirect their funds to finance educational tasks at the expense of other public activity areas? 4. Do the currently used algorithms for the distribution of subsidies reflect the real needs of local government units, and, as a result, there is an optimal allocation of public funds? …”
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Using Pleiades Satellite Imagery to Monitor Multi-Annual Coastal Dune Morphological Changes by Olivier Burvingt, Bruno Castelle, Vincent Marieu, Bertrand Lubac, Alexandre Nicolae Lerma, Nicolas Robin

“…Different technologies are currently used to monitor coastal dune topographic changes (GNSS, UAV, airborne LiDAR, etc.). …”
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Cerebrospinal Fluid Leakage Combined with Blood Biomarkers Predicts Poor Wound Healing After Posterior Lumbar Spinal Fusion: A Machine Learning Analysis by Pang Z, Ou Y, Liang J, Huang S, Chen J, Huang S, Wei Q, Liu Y, Qin H, Chen Y

“…By combining logistic regression analysis with six machine learning algorithms, this study identified six predictors associated with PWH: subcutaneous lumbar spine index(SLSI), albumin, postoperative glucose, cerebrospinal fluid leakage(CSFL), neutrophil (NEU), and C-reactive protein(CRP). …”
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RehabHand—A New Physical Rehabilitation Training Dataset: Construction and Benchmark Performances of the Relevant Hand Tasks by Sinh Huy Nguyen, Hoang Bach Nguyen, Thi Thu Hong Le, Chi Thanh Nguyen, Thi Thanh Huyen Nguyen, Quynh Tho Chu, Thi Lan Le, Thanh Hai Tran, Hai Vu

“…Physical training for a person with an impaired hand generally requires extensive guidance and supervision from rehabilitation therapists. Currently, the advantages of wearable sensing technologies and the breakthrough performances of deep neural networks offer feasible solutions for developing assistive tools, particularly to automatically monitor the functional use of the patient’s hand. …”
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Automated snow cover detection on mountain glaciers using spaceborne imagery and machine learning by R. Aberle, E. Enderlin, S. O'Neel, C. Florentine, L. Sass, A. Dickson, H.-P. Marshall, A. Flores

“…We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. …”
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PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorder... by Christine Knaevelsrud, Sebastian Burchert, Till Langhammer, Leona Hammelrath, Annette Brose, Manuel Heinrich, Pavle Zagorscak

“…PREACT channels state-of-the-art machine learning techniques identify predictors of non-response to CBT in ID. The study is currently running and will end in June 2026. Patients seeking CBT at one of four participating outpatient clinics are invited to join PREACT-digital. …”
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Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…Three widely applicable machine learning algorithms (Random Forests, Gradient Boosting Machine, and XGBoost) were used to screen the metrics, and then the corresponding predictive models were constructed using discriminative analysis, and the best performing model was selected as the target model. …”
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Predicting suicidality in people living with HIV in Uganda: a machine learning approach by Anthony B. Mutema, Anthony B. Mutema, Anthony B. Mutema, Lillian Linda, Lillian Linda, Daudi Jjingo, Segun Fatumo, Segun Fatumo, Eugene Kinyanda, Allan Kalungi, Allan Kalungi, Allan Kalungi

“…BackgroundPeople living with HIV (PLWH) are more likely to experience suicidal thoughts and exhibit suicidal behavior than the general population. However, there are currently no effective methods of predicting who is likely to experience suicidal thoughts and behavior. …”
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Development of Artificial Intelligence-Based Programs for the Diagnosis of Myocarditis in COVID-19 Using Chest Computed Tomography Data» by Ievgen A. Nastenko, Maksym O. Honcharuk, Vitalii O. Babenko, Mykola I. Lynnyk, Viktoria I. Ignatieva, Vitalii A. Yachnyk

“…It has been established that 7.2% of patients hospitalized with coronavirus disease (COVID-19) exhibit signs of heart disease, with 23% of these patients experiencing heart failure. Currently, there is a lack of data on chest computed tomography (CT) for diagnosing myocarditis associated with COVID-19. …”
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A machine learning-based screening model for the early detection of prostate cancer developed using serum microRNA data from a mixed cohort of 8,741 participants by Cong Lai, Zhensheng Hu, Zhuohang Li, Zhikai Wu, Kuiqing Li, Lin Li, Hongze Liu, Juanyi Shi, Yi Zhou, Kewei Xu, Cheng Liu

“…Abstract Objective Early detection of prostate cancer (PCa) can improve the prognosis of patients. Currently, the role of the prostate specific antigen test for PCa screening remains debatable. …”
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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of <i>T. japonicus</i> density. …”
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Characterization of Cuproptosis-Related LncRNAs Prognostic Signature and Identification of LINC02285 as a Novel Biomarker for Ovarian Cancer by Lei H, Zhou Z, Liu C, Chen W, Li Y, Shu G, Wang M, Guo K, Pan Q, Yin G

“…In-depth analyses exploring the relationship between CRLs and ovarian cancer (OC) are currently limited.Methods: LASSO-Cox regression analysis was conducted to assess the prognostic significance of CRLs and develop a cuproptosis-related prognostic model. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…In contrast, nuclear magnetic resonance (NMR) measurements, which provide information on pore body size distribution, are faster and can be leveraged to estimate capillary pressure using machine learning algorithms. Recently, artificial intelligence methods have also been applied to capillary pressure prediction (Qi et al., 2024).Currently, no readily applicable predictive model exists for estimating an entire capillary pressure curve directly from standard petrophysical logs and core data. …”
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Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis by Qiaofeng Chen, Yuanping Fan, Kaini Wu, Tianpan Cai, Chunyu Lan, Mingju Yu, Yunfeng Fu, Qi Zhu, Jianhao Qiu, Xiaodong Zhou

“…Three machine‐learning algorithms were used to develop radiomic signatures. …”
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Interleukin-4 and specific IgE to oranges levels study in persons with allergic anamnesis by A. S. Prilutskiy, N. B. Abylgazinova, K. Y. Tkachenko

“…Introduction. Currently allergic diseases pose a global health concern. …”
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Aplicación del análisis de rango reescalado R/S para la predicción de genes en el genoma vegetal Rescaled range R/S analysis application for genes prediction in the plant genome by Martha Isabel Almanza Pinzón, Karina López López, Carlos Eduardo Téllez Villa

“…Python programming language algorithms were developed with the purpose of extract, screen and modeling more than 80% of the registered gene sequences for these genomes in the NCBI Gene Bank data base. …”
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