High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery by Qi Ou, Hongshuai Wang, Minyang Zhuang, Shangqian Chen, Lele Liu, Ning Wang, Zhifeng Gao

“…We employed a 3D transformer-based molecular representation learning algorithm to create the Org-Mol pre-trained model, using 60 million semi-empirically optimized small organic molecule structures. …”
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The Marine Safety Simulation based Electronic Chart Display and Information System by Xin Yu Zhang, Yong Yin, Jin YiCheng, XiaoFeng Sun, Ren HongXiang

“…The man-machine conversation method is taken to amend planned route to obtain autodeciding of feasibility according to ECDIS information, and the route monitoring algorithm is improved by enhancing its precision caused by screen coordinate conversion. …”
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Ultrasound Assessment in Polycystic Ovary Syndrome Diagnosis: From Origins to Future Perspectives—A Comprehensive Review by Stefano Di Michele, Anna Maria Fulghesu, Elena Pittui, Martina Cordella, Gilda Sicilia, Giuseppina Mandurino, Maurizio Nicola D’Alterio, Salvatore Giovanni Vitale, Stefano Angioni

“…Studies on diagnostic criteria, imaging modalities, stromal assessment, and machine-learning algorithms were prioritized. Additional references were identified via citation screening. …”
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Interplay between tumor mutation burden and the tumor microenvironment predicts the prognosis of pan-cancer anti-PD-1/PD-L1 therapy by Wuyuan Liao, Wuyuan Liao, Wuyuan Liao, Xinwei Zhou, Xinwei Zhou, Hansen Lin, Hansen Lin, Zihao Feng, Zihao Feng, Xinyan Chen, Yuhang Chen, Yuhang Chen, Minyu Chen, Minyu Chen, Mingjie Lin, Mingjie Lin, Gaosheng Yao, Gaosheng Yao, Jinwei Chen, Jinwei Chen, Haoqian Feng, Haoqian Feng, Yinghan Wang, Yinghan Wang, Zhiping Tan, Zhiping Tan, Youyan Tan, Jun Lu, Jun Lu, Pengju Li, Pengju Li, Jinhuan Wei, Jinhuan Wei, Li Luo, Li Luo, Liangmin Fu, Liangmin Fu, Liangmin Fu

“…By incorporating the interaction between TMB and the TME, our model provides a more accurate prediction of patient prognosis and treatment response across multiple cancer types. …”
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Optimized Landing Site Selection at the Lunar South Pole: A Convolutional Neural Network Approach by Yongjiu Feng, Haoteng Li, Xiaohua Tong, Pengshuo Li, Rong Wang, Shurui Chen, Mengrong Xi, Jingbo Sun, Yuhao Wang, Huaiyu He, Chao Wang, Xiong Xu, Huan Xie, Yanmin Jin, Sicong Liu

“…The combined use of CNN and SHAP enables more effective potential site screening and a deeper understanding of the factors influencing selection. …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

“…The principal predictive feature variables were sex, maximum heart rate, and ST/HR index. Our model generated results within one minute after completing ExECG.ConclusionThe multimodal AI algorithm, leveraging deep learning techniques, efficiently and accurately identifies patients with significant CAD using ExECG data, aiding clinical screening in both symptomatic and asymptomatic patients. …”
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Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review by Mehrdad Rahsepar Meadi, Tomas Sillekens, Suzanne Metselaar, Anton van Balkom, Justin Bernstein, Neeltje Batelaan

“…When a concern occurred in more than 2 articles, we identified it as a distinct theme. …”
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Validating the recording of exacerbations of asthma in electronic health records: a systematic review protocol by Jennifer K Quint, Elizabeth Moore, Zakariah Z Gassasse

“…However, previous studies found significant heterogeneity in the algorithms used to define asthma exacerbations. Validating definitions of asthma exacerbations in EHR will lead to more robust and comparable evidence in future research.Methods and analysis Medline and Embase will be searched for the key concepts relating to asthma exacerbations, EHR and validation. …”
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IMPROVEMENT OF ADAPTATION TO STRUCTURES REMOVABLE DENTURES IN PATIENTS WITH ISCHEMIC HEART DISEASE by N.A. Ryabushko, V.N. Dvornik, I.V. Pavlish, G.N. Balya

“…The proposed health care was a complex algorithm to use: softener oral "Corsodyl" - 3-5 times a day after meals; clean teeth and dentures 2 times a day (morning and bedtime) toothpaste "Parodontax" and the bath solution Rinhra 3-5 times a day, with dryness in the mouth For the functional assessment made dentures were designed by us and proposed to use two methods of assessing patients to adapt designs removable dentures: • Objective evaluation - "Method of determining the degree of adaptation to the designs of removable dentures," Ukraine patent for utility model №101852 of 12.10.15; • Subjective evaluation - "Method of accelerated determination adaptation of patients to removable dentures designs using screening test" certificate of registration of copyright Ukraine №59280 15.04.2015. …”
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Identification for internal reference genes in different periods of granulosa cells of Tianfu meat geese by MO Yuanliang, WANG Yushi, WANG Jiwen

“…Therefore, the most stable internal reference genes were SDH and HMBS in granulosa cells at different developmental stages, and it could get more accurate normalization of RT-qPCR data by geometric averaging of the most stable reference genes.…”
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Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study by abbas Rezaianzadeh, Samane Nematolahi, maryam jalali, Shayan Rezaeianzadeh, Masoumeh Ghoddusi Johari, Seyed Vahid Hosseini

“…This model can be useful for early screening and improving preventive and curative health services in health promotion. …”
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Artificial Intelligence in Biomedical Sciences: A Scoping Review by Rasha Abu-El-Ruz, Ali Hasan, Dima Hijazi, Ovelia Masoud, Atiyeh M. Abdallah, Susu M. Zughaier, Maha Al-Asmakh, Maha Al-Asmakh

“…Scope (6): Opportunities and limitations of AI in biomedical sciences, where major reported opportunities include efficiency, accuracy, universal applicability, and real-world application. Limitations include; model complexity, limited applicability, and algorithm robustness.ConclusionAI has generally been under characterized in the biomedical sciences due to variability in AI models, disciplines, and perspectives of applicability.…”
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Module Partition of Mechatronic Products Based on Core Part Hierarchical Clustering and Non-Core Part Association Analysis by Shuai Wang, Yi-Fei Song, Guang-Yu Zou, Jia-Xiang Man

“…Firstly, the core part screening method is used to simplify the structural model of mechatronic products and reduce the difficulty of modeling. …”
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Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints by Xiumin Liu, Xinyue Zhang, Ye Sheng, Zihe Zhang, Pan Xiong, Xuehai Ju, Junwu Zhu, Caichao Ye

“…The random forest (RF) algorithm exhibited the best predictive performance for material design and screening. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Hence, the development of efficient automated DR grading systems is crucial for early screening and treatment. Although progress has been made in DR detection using deep learning techniques, these methods still face challenges in handling the complexity of DR lesion characteristics and the nuances in grading criteria. …”
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Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study by Jaclyn A Pagliaro, Lauren K Wash, Ka Ly, Jenny Mathew, Alison Leibowitz, Ryan Cabrera, Jolie B Wormwood, Varsha G Vimalananda

“…ResultsOf the 7714 who were mailed a study invitation, 560 were screened. Of the screened patients, 203 were enrolled (2.9% enrollment yield) and 166 completed the study (82% retention rate). …”
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The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…IntroductionObstructive sleep apnea (OSA) is a prevalent sleep disorder with a high rate of undiagnosed patients, primarily due to the complexity of its diagnosis made by polysomnography (PSG). Considering the severe comorbidities associated with OSA, especially in the cardiovascular system, the development of early screening tools for this disease is imperative. …”
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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…The Boruta algorithm was used for feature selection, and model performance was evaluated using cross-validation and a validation set. …”
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Deep learning system for the auxiliary diagnosis of thyroid eye disease: evaluation of ocular inflammation, eyelid retraction, and eye movement disorder by Yu Han, Jun Xie, Xiaoyu Li, Xinying Xu, Bin Sun, Han Liu, Chunfang Yan

“…The designed quantitative algorithm provides greater interpretability than existing studies, thereby validating the effectiveness of the diagnostic system.ConclusionThe deep learning-based auxiliary diagnostic model for TED established in this study exhibits high accuracy and interpretability in the diagnosis of ocular inflammation related to CAS, eyelid retraction, and eye movement disorders. …”
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High-performance computing for static security assessment of large power systems by Venkateswara Rao Kagita, Sanjaya Kumar Panda, Ram Krishan, P. Deepak Reddy, Jabba Aswanth

“…We perform extensive experiments to evaluate the efficacy of the proposed algorithm. As a result, we establish that the proposed parallel algorithm with high-performance computing (HPC) computing is much faster than the traditional algorithms. …”
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