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    InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

    Published 2025-02-01
    “…Predicting drug-target binding affinity via in silico methods is crucial in drug discovery. Traditional machine learning relies on manually engineered features from limited data, leading to suboptimal performance. …”
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    Experimental Determination and Comparative Analysis of the PPH030GP, ABS and PLA Polymer Strength Characteristics at Different Strain Rates by M. Yu. Zalohin, V. V. Skliarov, Ja. S. Dovzhenko, D. A. Brega

    Published 2019-07-01
    “…Regarding to this information, engineering companies that design parts of the automotive industry should have polymer material characteristics over an entire range of deformations up to destruction for their performance prediction. …”
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    Streamlining medical software development with CARE lifecycle and CARE agent: an AI-driven technology readiness level assessment tool by Steven N. Hart, Patrick L. Day, Christopher A. Garcia

    Published 2025-07-01
    “…Key institutional stakeholders—including clinical informatics experts, data engineers, ethicists, and operational leaders—were engaged to identify and prioritize the regulatory, ethical, and technical requirements unique to clinical AI/ML development. …”
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