Search Results - "machine learning"

New Mechanism Explanation, Emergence and Reduction /

Subjects: “…Machine learning.…”
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On the path to AI Law's prophecies and the conceptual foundations of the machine learning age by Grant, Thomas D.

Subjects: “…Machine learning…”
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On the path to AI Law's prophecies and the conceptual foundations of the machine learning age by Grant, Thomas D.

Subjects: “…Machine learning…”
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OAPEN Library: description of the publication

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning by Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida, Hikaru Nakazawa, Sakiya Kawada, Hafumi Nishi, Koji Tsuda, Tomoshi Kameda, Mitsuo Umetsu

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Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis by Elias Aboujaoude, Germano Vera Cruz, Lucien Rochat, Robert Courtois, Farah Ben Brahim, Riaz Khan, Yasser Khazaal

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Quantitative peritumoral magnetic resonance imaging fingerprinting improves machine learning-based prediction of overall survival in colorectal cancer by Azadeh Tabari, Brian D'Amore, Janice Noh, Michael S. Gee, Dania Daye

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Machine learning analysis to predict health outcomes among emergency department users in Southern Brazil: a protocol study by Bruno Pereira Nunes, João Vissoci, Felipe Mendes Delpino, Pablo Stolz, Sabrina Ribeiro Farias, Bruna Borges Coelho, Indiara da Silva Viegas, Denis Carlos Carvalho Junior, Camila Sebaje da Silva Dias, Ana Paula Santana Coelho Almeida, Luiz Augusto Facchini, Alexandre Dias Porto Chiavegatto Filho

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Establishment and Analysis of an Artificial Neural Network Model for Early Detection of Polycystic Ovary Syndrome Using Machine Learning Techniques by Wu Y, Xiao Q, Wang S, Xu H, Fang Y

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Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review by Maleeha Naseem, Ramsha Akhund, Hajra Arshad, Muhammad Talal Ibrahim

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A Study to Analyse Covid-19 Outbreak Using Multiple Linear Regression: A Supervised Machine Learning Approach by Jayanti Semwal, Abhinav Bahuguna, Akanksha Uniyal, Shaili Vyas

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Machine Learning to Predict the 1-Year Mortality Rate After Acute Anterior Myocardial Infarction in Chinese Patients [Corrigendum] by Li Y, Jiang L, He J, Jia K, Peng Y, Chen M

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Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study by Siyang Zeng, Mehrdad Arjomandi, Yao Tong, Zachary C Liao, Gang Luo

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Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study by Ullah, Zahid, Saleem, Farrukh, Jamjoom, Mona, Fakieh, Bahjat

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Genetic algorithm-assisted machine learning for clinical pregnancy prediction in in vitro fertilizationAJOG Global Reports at a Glance by Claudio Michael Louis, SKom, BEng, Nining Handayani, DVM, MBiomed, Tri Aprilliana, BPH, Arie A. Polim, MD, SpOG, DMAS, MBHRE, Arief Boediono, DVM, PhD, Ivan Sini, MD, FRANZOG, GDRM, MMIS, SpOG

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Mental issues, internet addiction and quality of life predict burnout among Hungarian teachers: a machine learning analysis by Gergely Feher, Krisztian Kapus, Antal Tibold, Zoltan Banko, Gyula Berke, Boroka Gacs, Imre Varadi, Rita Nyulas, Andras Matuz

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Can adverse childhood experiences predict chronic health conditions? Development of trauma-informed, explainable machine learning models by Hanin B. Afzal, Tasfia Jahangir, Yiyang Mei, Annabelle Madden, Abeed Sarker, Sangmi Kim

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Salivary cystatin S levels in children with early childhood caries in comparison with caries-free children; statistical analysis and machine learning by Maryam Koopaie, Mahsa Salamati, Roshanak Montazeri, Mansour Davoudi, Sajad Kolahdooz

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Using a Machine Learning Approach to Identify Low-Frequency and Rare FLG Alleles Associated with Remission of Atopic Dermatitis by Ronald Berna, Nandita Mitra, Ole Hoffstad, Bradley Wubbenhorst, Katherine L. Nathanson, David J. Margolis

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Comprehensive Metabolomics and Machine Learning Identify Profound Oxidative Stress and Inflammation Signatures in Hypertensive Patients with Obstructive Sleep Apnea by Zhiyong Du, Haili Sun, Yunhui Du, Linyi Li, Qianwen Lv, Huahui Yu, Fan Li, Yu Wang, Xiaolu Jiao, Chaowei Hu, Yanwen Qin

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Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation by Ya-Ting Lu, Horng-Jiun Chao, Yi-Chun Chiang, Hsiang-Yin Chen

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