Search Results

Deleterious synonymous mutation identification based on selective ensemble strategy.

• Authors : Wang, Lihua^1,2 (AUTHOR); Zhang, Tao² (AUTHOR); Yu, Lihong³ (AUTHOR)

Subjects: MEDICAL genomics; SOURCE code; INDEPENDENT sets

• Source: Briefings in Bioinformatics. Jan2023, Vol. 24 Issue 1, p1-8. 8p.

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An Ensemble Framework for Improving the Prediction of Deleterious Synonymous Mutation.

• Authors : Cheng, Na; Wang, Huadong; Tang, Xi

Subjects: MEDICAL genomics; FUNCTIONAL groups; MACHINE learning

• Source: IEEE Transactions on Circuits & Systems for Video Technology. May2022, Vol. 32 Issue 5, p2603-2611. 9p.

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Underspecification Presents Challenges for Credibility in Modern Machine Learning.

• Authors : D'Amour, Alexander; Heller, Katherine; Moldovan, Dan

Subjects: MEDICAL genomics; ELECTRONIC health records; MACHINE learning

• Source: Journal of Machine Learning Research. 2022, Vol. 23, p1-61. 61p.

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WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

• Authors : Vatsyayan, Aastha; Kumar, Mukesh; Saikia, Bhaskar Jyoti

Subjects: NUCLEOTIDE sequencing; HEPATOLENTICULAR degeneration; MACHINE learning

• Source: PLoS ONE; 5/17/2024, Vol. 19 Issue 5, p1-14, 14p

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Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning.

• Authors : Murali V; Department of Computer Science and Engineering, Amrita School of Engineering, Bengaluru, India.; Muralidhar YP

Subjects: Algorithms* ; Machine Learning*; Databases, Factual

• Source: Chemical biology & drug design [Chem Biol Drug Des] 2022 Aug; Vol. 100 (2), pp. 169-184. Date of Electronic Publication: 2022 May 30.Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 101262549 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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Findings from Sun Yat-sen University Provide New Insights into Bioinformatics (Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis).

Subjects: BIPOLAR disorder; INFORMATION technology; TECHNOLOGICAL innovations

• Source: Mental Health Weekly Digest; 10/4/2024, p269-269, 1p

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Data from Central South University Provide New Insights into Rosacea (Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning).

Subjects: MEDICAL genomics; TECHNOLOGICAL innovations; CONNECTIVE tissue diseases

• Source: Genomics & Genetics Weekly; 10/4/2024, p154-154, 1p

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Study Results from Mayo Clinic Update Understanding of Artificial Intelligence (Exploring stakeholder perceptions about using artificial intelligence for the diagnosis of rare and atypical infections).

Subjects: TECHNOLOGICAL innovations; ARTIFICIAL intelligence; MACHINE learning

• Source: Health & Medicine Week; 11/15/2024, p7721-7721, 1p

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Evaluation of different approaches for missing data imputation on features associated to genomic data.

• Authors : Petrazzini, Ben Omega; Naya, Hugo; Lopez-Bello, Fernando

Subjects: MISSING data (Statistics); RANDOM forest algorithms; MEDICAL genomics

• Source: BioData Mining; 9/3/2021, Vol. 14 Issue 1, p1-13, 13p

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Reports from Guangzhou University of Chinese Medicine Add New Study Findings to Research in Atopic Dermatitis (Construction and verification of atopic dermatitis diagnostic model based on pyroptosis related biological markers using machine...).

Subjects: ATOPIC dermatitis; BIOMARKERS; CHINESE medicine

• Source: Genomics & Genetics Weekly; 7/7/2023, p1209-1209, 1p

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