Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result by Michael J. Morris, Sheila A. Habib, Maggie L. Do Valle, John E. Schneider

“…**Objectives:** This study evaluated the potential cost savings for US payers of CyPath® Lung, a novel diagnostic tool utilizing flow cytometry and machine learning for the early detection of lung cancer, in patients with positive LDCT scans with indeterminate pulmonary nodules (IPNs) ranging from 6 to 29 mm. …”
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Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…Study focus: Large-scale and high-precision estimation of water quality parameters (WQPs) is critical in explaining the spatiotemporal dynamics and clarifying their response to short-term hydrometeorological factors. Six machine learning models optimized by intelligent optimization algorithms (IOA-ML) were developed to retrieve WQPs using paired in situ measurements and near-synchronous Sentinel-2 reflectance (Rrs). …”
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Clinical Holistic Medicine: the “New Medicine”, the Multiparadigmatic Physician, and the Medical Record by Søren Ventegodt, Mohammed Morad, Joav Merrick

“…Reflection: To keep track of facts, to provide an overview, to encourage causal analysis, to support research and learning, and to reveal mistakes easily. B. Communication: To communicate with the patient with a printout of the case record to create trust and help the patient to remember all assignments and exercises. …”
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Prevalence and level of stress among final-year students at a health science institute in Bangladesh by Md. Jonaied Alam, Mahmudul Islam Khan Pratik, Abid Hasan Khan, Muhammad Shahidul Islam, Muhammad Millat Hossain

“…This implies that the educational system, means of teaching, teaching materials, teachers as well as the services provided by the institutions cannot provide a conducive environment for effective learning as well as creating a secure future for the students as long as they can cope with the academic pressure. …”
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Selective inhibition of TGF-β-induced epithelial-mesenchymal transition overcomes chemotherapy resistance in high-risk lung squamous cell carcinoma by Liangdong Sun, Jue Wang, Huansha Yu, Xinsheng Zhu, Jing Zhang, Junjie Hu, Yilv Yan, Xun Zhang, Yuming Zhu, Gening Jiang, Ming Ding, Peng Zhang, Lele Zhang

“…The integrative development of machine learning-based models reveals a random survival forest (RSF) prognostic model for LUSC. …”
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Acute Deterioration of Pulmonary Arterial Hypertension (PAH) in a Patient with Neurofibromatosis Type 1 (NF1) by Seiya Tanaka, Fuko Kawahara, Taro Miyamoto, Satoshi Tsurusaki, Yoshihito Sanuki, Kiyoshi Ozumi, Takashi Harada, Hiromi Tasaki

“…Mean pulmonary arterial pressure rapidly improved. Learning Objective. Pulmonary arterial hypertension (PAH) in neurofibromatosis type 1 (NF1) can occur due to lung disease or due to certain involvement of pulmonary arteries, or a combination of both. …”
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Cross-modal feature interaction network for heterogeneous change detection by Zhiwei Yang, Xiaoqin Wang, Haihan Lin, Mengmeng Li, Mengjing Lin

“…Recently, research has focused on feature space translation methods based on deep learning technology for heterogeneous images. However, these types of methods often lead to the loss of original image information, and the translated features cannot be efficiently compared, further limiting the accuracy of change detection. …”
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Effect of vascular simulation training on practice performance in residents: a retrospective cohort study by Lin Yang, Jianlin Liu, Yanzi Li, Yamin Liu

“…At the end of the assessment, the learning time for angiography (3.65±0.64 vs 4.07±0.77 months) and the complete procedure time (33.81±10.11 vs 41.32±12.56 min) were lower in the ST group than in the CT group (p<0.01). …”
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A longitudinal study on the professional identity formation of health promotion practitioners: evidence from undergraduate students in Switzerland by Verena Biehl, Verena Biehl, Andreas Bänziger, Frank Wieber, Frank Wieber

“…Given the importance of a strong PI, the following interventions are suggested to strengthen health promotion students’ PI: (1) incorporating PI formation as a learning objective within curricula, and (2) enhancing the visibility and clarity of health promotion’s professional profile within undergraduate studies and in society. …”
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Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments by Somayajulu L.N. Dhulipala, Nicholas Casaprima, Audrey Olivier, Bjorn C. Vaagensmith, Timothy R. McJunkin, Ryan C. Hruska

“…Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. …”
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A Physics-Informed Cold-Start Capability for xEV Charging Recommender System by Raik Orbay, Aditya Pratap Singh, Johannes Emilsson, Michele Becciani, Evelina Wikner, Victor Gustafson, Torbjorn Thiringer

“…Matching a unsupervised learning based clustering pipeline for 7 possible customer driving styles, an RS agent can prescribe 7 charging power transients automatically and cold-start the RS until more data is available.…”
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Development and Validation of Rabies Health Education Module (RaHEM) for Dog Owners in Kelantan, Malaysia: An ADDIE Model by Mohammad Fazrul Mohammad Basir, Suhaily Mohd Hairon, Mohd Ismail Ibrahim, Wan Mohd Zahiruddin Wan Mohamad, Nik Mohd Hafiz Mohd Fuzi, Ainin Syakirah Rosli, Mohammad Sabri Abdul Rahman, Anas Rosedi

“…The module’s content was designed and developed based on the Modified Health Belief Model and Mayer’s Cognitive Theory of Multimedia Learning. Validation was performed by a panel of six experts and ten dog owners through content and face validity indices, respectively. …”
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A mixed methods crossover randomized controlled trial exploring the experiences, perceptions, and usability of artificial intelligence (ChatGPT) in health sciences education by Mirella Veras, Joseph-Omer Dyer, Holly Shannon, Bryce J M Bogie, Morgan Ronney, Harmehr Sekhon, Derek Rutherford, Paulo Goberlânio Barros Silva, Dahlia Kairy

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Motor and Perceptual Recovery in Adult Patients with Mild Intellectual Disability by Mariagiovanna Cantone, Maria A. Catalano, Giuseppe Lanza, Gaetano La Delfa, Raffaele Ferri, Manuela Pennisi, Rita Bella, Giovanni Pennisi, Alessia Bramanti

“…Multimodal integrated interventions targeting visual-perceptual abilities and motor skills are an effective neurorehabilitative approach in adult patients with mild ID. Motor learning and memory-mediated mechanisms of neural plasticity might underlie the observed recovery, suggesting the presence of plastic adaptive changes even in the adult brain with ID.…”
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Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In the factory-based recirculating water high-density aquaculture environment, images have disadvantages such as uneven contrast and blurring, and there are difficulties in manually extracting image features. Although the deep learning-based fish feeding intensity assessment model has higher recognition accuracy and better robustness, the conventional differentiation of feeding intensity usually relies on manual experience to divide the feeding intensity dataset, which is subjective and uncertain, and the annotation is observed by the aquaculture experienced personnel to increase the labor and time cost. …”
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Investigation of sensory attenuation in the somatosensory domain using EEG in a novel virtual reality paradigm by Gianluigi Giannini, Till Nierhaus, Felix Blankenburg

“…Furthermore, we modulated the expectation of receiving a somatosensory stimulation across self-production and passive perception through a simple probabilistic learning task, allowing us to test to what extent the electrophysiological correlates of sensory attenuation are impacted by stimulus expectation. …”
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Development of risk models for early detection and prediction of chronic kidney disease in clinical settings by Pegah Bahrami, Davoud Tanbakuchi, Monavar Afzalaghaee, Majid Ghayour-Mobarhan, Habibollah Esmaily

“…Therefore, this study aims to utilize machine learning techniques to predict CKD at early stages. …”
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Multilocus Sequence Typing for Interpreting Blood Isolates of Staphylococcus epidermidis by Prannda Sharma, Ashley E. Satorius, Marika R. Raff, Adriana Rivera, Duane W. Newton, John G. Younger

“…Here, we examined 100 isolates of this species (50 blood isolates representing true bacteremia, 25 likely contaminant isolates, and 25 skin isolates) and the ability of sequence typing to differentiate them. Three machine learning algorithms (classification regression tree, support vector machine, and nearest neighbor) were employed. …”
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Multi-organ frailty is enhanced by periodontitis-induced inflammaging by Yoshitaka Kase, Satoru Morikawa, Yuji Okano, Tatsuya Hosoi, Takazumi Yasui, Yoko Taki-Miyashita, Mitsutaka Yakabe, Maraku Goto, Kazuyuki Ishihara, Sumito Ogawa, Taneaki Nakagawa, Hideyuki Okano

“…Cognitive function assessment revealed increased activated microglia and decreased adult neurogenesis in the hippocampus, impairing spatial learning. Thus, periodontitis induced both physical and cognitive frailties. …”
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A data-driven intelligent fault diagnosis framework for permanent magnet in PMSM by Huizhen Wang, Lei Wang, QiYa Wu, Haoying Pei, Lijun Diao

“…Furthermore, ensemble learning integrates the outputs of multiple base learners to enhance generalization. …”
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