Deaths ascribed to non-communicable diseases among rural Kenyan adults are proportionately increasing: evidence from a health and demographic surveillance system, 2003-2010. by Penelope A Phillips-Howard, Kayla F Laserson, Nyaguara Amek, Caryl M Beynon, Sonia Y Angell, Sammy Khagayi, Peter Byass, Mary J Hamel, Anne M van Eijk, Emily Zielinski-Gutierrez, Laurence Slutsker, Kevin M De Cock, John Vulule, Frank O Odhiambo

“…<h4>Background</h4>Non-communicable diseases (NCDs) result in more deaths globally than other causes. Monitoring systems require strengthening to attribute the NCD burden and deaths in low and middle-income countries (LMICs). …”
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Problems and perspectives of family doctors training on the undergraduate stage by Yu. M. Kolesnik, V. D. Syvolap, N. S. Mikhaylovskaya, T.O. Kulinich

“…The introduction of family medicine requires more training of highly qualified personnel, which should begin at undergraduate stage, using both traditional forms of learning, innovative technologies based on the experience of other medical institutions of Ukraine and the world.…”
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Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis by Ivars Neiders, Signe Mežinska, Neeltje E. M. van Haren

“…First, there are issues that should deserve more attention than they have received thus far (clinical utility, extensive or mandatory use). …”
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Amyloid Cardiomyopathy: Review of A Fatal Case Report by O. V. Soldatova, I. Ya. Goryanskaya

“…To date, it has been proven that amyloid cardiomyopathy is an important and often undiagnosed cause of chronic heart failure and cardiac arrhythmias, especially in the elderly. There are more than 15 types of precursor proteins capable of causing systemic amyloidosis, but only 2 of them accumulate in the interstitium of the heart: light chains of clonal immunoglobulin (AL) and tetrameric protein transthyretin (TTR). …”
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Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease by Weizhe Zhen, Yu Wang, Hongjun Zhen, Weihe Zhang, Wen Shao, Yu Sun, Yanan Qiao, Shuhong Jia, Zhi Zhou, Yuye Wang, Leian Chen, Jiali Zhang, Dantao Peng, Dantao Peng

“…In the non-AD group, the trend of pathologic product levels with age was consistently opposite to that of the AD group. We finally screened the optimal AD diagnostic model (AUC=0.959) based on the results of correlation analysis and by using the Xgboost algorithm and SVM algorithm.ConclusionIn a novel finding, we observed that Tau protein and Aβ had opposite trends with age in both the AD and non-AD groups. …”
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Iron Ore Information Extraction Based on CNN-LSTM Composite Deep Learning Model by Haili Chen, Mengxiang Xia, Yaping Zhang, Ruonan Zhao, Bingran Song, Yang Bai

“…The bands are subsequently screened by correlation analysis, successive projections algorithm (SPA), and competitive adaptive reweighted sampling (CARS), down to 50 dimensions using principal component analysis (PCA). …”
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Transmitted drug resistance in the CFAR network of integrated clinical systems cohort: prevalence and effects on pre-therapy CD4 and viral load. by Art F Y Poon, Jeannette L Aldous, W Christopher Mathews, Mari Kitahata, James S Kahn, Michael S Saag, Benigno Rodríguez, Stephen L Boswell, Simon D W Frost, Richard H Haubrich

“…Human immunodeficiency virus type 1 (HIV-1) genomes often carry one or more mutations associated with drug resistance upon transmission into a therapy-naïve individual. …”
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Development of an MRI based artificial intelligence model for the identification of underlying atrial fibrillation after ischemic stroke: a multicenter proof-of-concept analysisRes... by Zijie Zhang, Yang Ding, Kaibin Lin, Wenli Ban, Luyue Ding, Yudong Sun, Chuanliang Fu, Yihang Ren, Can Han, Xue Zhang, Xiaoer Wei, Shundong Hu, Yuwu Zhao, Li Cao, Jun Wang, Saman Nazarian, Ying Cao, Lan Zheng, Min Zhang, Jianliang Fu, Jingbo Li, Xiang Han, Dahong Qian, Dong Huang

“…Between January 1, 2018 and December 31, 2021, 510 patients were retrospectively enrolled for algorithm development and performance was measured using fivefold cross-validation. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…We also wanted to know whether adding phone calls from a physiotherapist made the website more effective. Finally, we explored whether these options would represent ‘good value for money’ for the National Health Service. …”
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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

“…These person-centred approaches to T2DM management, which are more effective and personalized than some traditional strategies, only work because of the often-hidden synergies between AI algorithms in areas such as diagnostic criteria, predictive methods, and familiar classification tools for subgroups with relevant aspects/predictors on prognosis or treatment responsiveness.…”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…Exclusion criteria involved studies older than 20 years or lacking direct relevance. After screening 33 core articles and identifying 13 more through citation tracking, 46 articles were included in the final review.ResultsThis narrative review describes the characteristics of sedentary behavior, associated health risks, and the applications of ML in this context. …”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…Computational data methods could be used to reduce the cost and time involved in experimental drug discovery, allowing researchers to simulate biological interactions and screen large compound libraries more efficiently. …”
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Neutrophil extracellular traps-related genes contribute to sepsis-associated acute kidney injury by Tang Shaoqun, Yu Xi, Wang Wei, Luo Yaru, Lei Shaoqing, Qiu Zhen, Yang Yanlin, Sun Qian, Xia Zhongyuan

“…Differentially expressed genes were screened by “limma” package in R. Least absolute shrinkage and selection operator algorithm was applied to identify the hub genes. …”
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Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…Abstract This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. …”
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Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study by Ting Peng, Rujia Miao, Hao Xiong, Yanhui Lin, Duzhen Fan, Jiayi Ren, Jiangang Wang, Yuan Li, Jianwen Chen

“…A total of 5 machine learning algorithms, namely random forest, Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting, Gradient Boosting Machine, and CatBoost were used. …”
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Poor Nutritional Status Increases Risk of Postoperative Adverse Events after Surgical Management of Traumatic Ankle Fracture by Sanket Mehta MD, Nicholas Danford MD

“…Patients with poor nutritional status were older (56 vs. 51 years), more likely to present in shock (7.5% vs. 2.3%) and due to motor vehicle collision mechanism (all P< 0.001). …”
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Helicobacter pylori eradication treatment for gastric carcinoma prevention in asymptomatic or dyspeptic adults: systematic review and Bayesian meta-analysis of randomised controlle... by Teruhiko Terasawa, Isao Miyashiro, Katsuaki Kato, Takaki Yoshikawa, Reo Takaku, Hiroshi Nishida

“…However, concerns about supporting unfocused screening and eradication programme in healthy, asymptomatic populations have arisen. …”
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Maternal factors associated with early-onset neonatal sepsis among caesarean-delivered babies at Mbarara Regional Referral Hospital, Uganda: a case-control study by James M. Maisaba, Richard Migisha, Asiphas Owaraganise, Leevan Tibaijuka, David Collins Agaba, Joy Muhumuza, Joseph Ngonzi, Stella Kyoyagala, Musa Kayondo

“…We enrolled mother-baby pairs for both groups, obtaining maternal data via structured questionnaires The diagnosis of EONS was made using the WHO Young Infant Integrated Management of Childhood Illnesses algorithm. …”
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A systematic review of neural network applications for groundwater level prediction by Samuel K. Afful, Cyril D. Boateng, Emmanuel Ahene, Jeffrey N. A. Aryee, David D. Wemegah, Solomon S. R. Gidigasu, Akyana Britwum, Marian A. Osei, Jesse Gilbert, Haoulata Touré, Vera Mensah

“…In conclusion, a hybrid metaheuristic algorithm produced more efficient results emphasizing their efficacy. …”
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ST-YOLO: a deep learning based intelligent identification model for salt tolerance of wild rice seedlings by Qiong Yao, Qiong Yao, Pan Pan, Pan Pan, Xiaoming Zheng, Xiaoming Zheng, Guomin Zhou, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Diversified feature extraction paths are introduced to enhance the ability of feature extraction; Introducing CAFM (Context Aware Feature Modulation) convolution and attention fusion modules into the backbone network to enhance feature representation capabilities while improving the fusion of features at various scales; Design a more flexible and effective spatial pyramid pooling layer using deformable convolution and spatial information enhancement modules to improve the model’s ability to represent target features and detection accuracy.ResultsThe experimental results show that the improved algorithm improves the average precision by 2.7% compared with the original network; the accuracy rate improves by 3.5%; and the recall rate improves by 4.9%.ConclusionThe experimental results show that the improved model significantly improves in precision compared with the current mainstream model, and the model evaluates the salt tolerance level of wild rice varieties, and screens out a total of 2 varieties that are extremely salt tolerant and 7 varieties that are salt tolerant, which meets the real-time requirements, and has a certain reference value for the practical application.…”
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