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Giuseppe Pontillo, Giuseppe Pontillo, Simone Penna, Simone Penna, Sirio Cocozza, Sirio Cocozza, Mario Quarantelli, Mario Quarantelli, Michela Gravina, Michela Gravina, Roberta Lanzillo, Roberta Lanzillo, Stefano Marrone, Stefano Marrone, Teresa Costabile, Teresa Costabile, Matilde Inglese, Matilde Inglese, Vincenzo Brescia Morra, Vincenzo Brescia Morra, Daniele Riccio, Daniele Riccio, Andrea Elefante, Andrea Elefante, Maria Petracca, Maria Petracca, Carlo Sansone, Carlo Sansone, Arturo Brunetti, Arturo Brunetti

European radiology 2022;32(8):5382-5391

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Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

Satoshi Koide, Chie Imamura, Keisuke Kawano

IEEE/ACM transactions on computational biology and bioinformatics 2021;17(5):1762-1772

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Distinct metabolic phenotypes in adolescents with obesity identified by unsupervised learning: associations with insulin resistance and resting energy expenditure.

Anelise Sonza, Sofia Tamini, Adele Bondesan, Diana Caroli, Laura Abbruzzese, Alessandro Sartorio

Frontiers in endocrinology 2026;17():1875870

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Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.

Yuansong Zhu, Chuiguo Huang, Suxin Luo, Zhenxian Xiang, Wei Zhou, Weifeng Hong, Jian Shen, Yuzhou Xue

Lipids in health and disease 2021;20(1):48

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Results for ""Unsupervised Machine Learning""[mesh_terms]

Underwater Target Detection Utilizing Polarization Image Fusion Algorithm Based on Unsupervised Learning and Attention Mechanism.

Feature selection for unsupervised machine learning of accelerometer data physical activity clusters - A systematic review.

Unsupervised machine learning highlights the challenges of subtyping disorders of gut-brain interaction.

Spectral consensus strategy for accurate reconstruction of large biological networks.

Generative models for protein sequence modeling: recent advances and future directions.

Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction.

A comparative study of supervised and unsupervised machine learning algorithms applied to human microbiome.

Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach.

Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

Distinct metabolic phenotypes in adolescents with obesity identified by unsupervised learning: associations with insulin resistance and resting energy expenditure.

Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.

Results for
""Unsupervised Machine Learning""[mesh_terms]