From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer’s Disease and Other Neurological Disorders by Mashael A. Alghamdi

“…Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. …”
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Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems by Natalya Denissova, Serik Nurakynov, Olga Petrova, Daniker Chepashev, Gulzhan Daumova, Alena Yelisseyeva

“…The analysis involved screening relevant studies on remote sensing, avalanche dynamics, and data processing techniques. …”
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Multimodal ultrasound radiomics containing microflow images for the prediction of central lymph node metastasis in papillary thyroid carcinoma by Jiangyuan Ben, Jiangyuan Ben, Qiying Yv, Pengfei Zhu, Junhao Ren, Pu Zhou, Guifang Chen, Ying He, Ying He

“…The same methods were applied to screen clinical features. Nine ML algorithms were used to construct clinical models, radiomics models and fusion models. …”
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Application of Elastic networks and Bayesian networks to explore influencing factors associated with arthritis in middle-aged and older adults in the Chinese community by Tao Zhong, Tianlun Li, Jiapei Hu, Jiayi Hu, Li Jin, Yuxuan Xie, Bin Ma, Bin Ma, Dailun Hu

“…First, Elastic networks (ENs) were used to screen for features closely associated with arthritis, and we subsequently incorporated these features into the construction of the BNs model. …”
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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

“…We sought to feed common clinical available data to a deep learning algorithm for predicting short to long-term mortality in sepsis survivors. …”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Conventional software such as Turnitin and iThenticate have come a long way, using deep learning algorithms to identify more evolved instances of academic fraud, including paraphrasing plagiarism and AI-generated content. …”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Moreover, it addresses the black box problem since the predictions are described to the end users thanks to the combination of LLMS with interpretable ML models (i.e. tree-based algorithms) using feature importance and natural language. …”
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The Future of Minimally Invasive GI and Capsule Diagnostics (REFLECT), October 2024 by Lea Østergaard Hansen, Alexandra Agache, Anastasios Koulaouzidis

“…The symposium also highlighted the significance of predictive models for patient selection and developments in panenteric CE. …”
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High prevalence of resistance to macrolides and fluoroquinolones in Mycoplasma genitalium isolated from patients in two Russian megalopolises – Moscow and St. Petersburg in 2021– 2... by Edelstein I.A., Gushchin A.E., Gladin D.P., Romanov A.V., Negasheva E.S., Frigo N.V., Kozlov R.S., Potekaev N.N., Kozlova N.S., Borukhovich D.G.

“…The introduction of adapted diagnostic and therapeutic algorithms will reduce the duration of drug administration, increase the effectiveness of therapy and reduce the burden on the health care system. …”
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Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

“…Immunotherapy prediction models suggested a more favorable response to PD-1 treatment in the low IL1RAP expression group. …”
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Plasma metabolite biomarker identification study for the early detection of gastric cancer by Juan Zhu, Yida Huang, Bin Liu, Xue Li, Li Yuan, Le Wang, Kun Qian, Yingying Mao, Lingbin Du, Xiangdong Cheng

“…Ultra-performance liquid chromatography–mass spectrometry–based metabolomics methods were used to characterize the subjects’ plasma metabolic profiles and to screen and validate the GC biomarkers. Five machine learning algorithms (neural network, support vector machine, ridge regression, lasso regression and Naïve Bayes) were used to build a diagnostic model. …”
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Biomarker-driven drug repurposing for NAFLD-associated hepatocellular carcinoma using machine learning integrated ensemble feature selection by Subhajit Ghosh, Sukhen Das Mandal, Subarna Thakur

“…The incidence of non-alcoholic fatty liver disease (NAFLD), encompassing the more severe non-alcoholic steatohepatitis (NASH), is rising alongside the surges in diabetes and obesity. …”
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Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

“…This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. …”
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Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

“…The center of gravity method is used to address demand when constructing the quantitative function of out‐of‐stock loss. The NSGA‐II algorithm was selected to generate the results after the method comparison to ultimately determine the Pareto solution of the model. …”
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Leveraging diverse cell-death patterns to predict to predict prognosis and immunotherapy in hepatocellular carcinoma by Xiaoxiang Zhang, Dongxiao Ding, Dianqian Wang, Yunsheng Qin

“…The immune infiltration status and immune function of the signature were analyzed by ESTIMATE algorithm and ssGSEA algorithm. TIDE score, IPS and immune checkpoints expression and IC50 value were utilized to predict chemosensitivity and immunotherapy response. …”
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Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

“…These data support in-home use of the PRX VFT by the eye care provider for screening and monitoring in glaucoma, and may be extended to the screening and monitoring of other retinal, optic nerve and neurological diseases.Keywords: visual field test, glaucoma, home healthcare, prospective clinical trial…”
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Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning by Sijia Liu, Jiawei Luo, Chengqi He

“…Then, based on the key features screened out, a dynamic treatment recommendation system was constructed by using deep reinforcement learning algorithms, including Deep Deterministic Policy Gradien(DDPG), Deep Q-Network(DQN) and Batch-Constrained Q-learning(BCQ). …”
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Role of arachidonic acid metabolism in osteosarcoma prognosis by integrating WGCNA and bioinformatics analysis by Yaling Wang, Peichun HSU, Haiyan Hu, Feng Lin, Xiaokang Wei

“…An AA metabolism predictive model of the five AAMRGs were established by Cox regression and the LASSO algorithm. …”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…A prognostic model was constructed based on five selected IL(R)s using the LASSO Cox regression algorithm. …”
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