Results 201 to 210 of about 71,999 (265)

Monitoring of Geographic Atrophy Progression in Age-Related Macular Degeneration Using Fluorescence Lifetime Imaging Ophthalmoscopy. [PDF]

Invest Ophthalmol Vis Sci
Sagurski N, Jaggi D, Lincke JB, Wolf S, Zinkernagel MS, Dysli C.   +5 more
europepmc   +1 more source

Invisible Scar: Why Pregnancy History Matters for Women's Cardiovascular Health. [PDF]

Hypertension
Yanes Cardozo LL, Romero DG.
europepmc   +1 more source

The value of preoperative risk scores prior to tricuspid valve interventions: The TRI-SCORE and beyond. [PDF]

Ann Cardiothorac Surg
Dreyfus J, Messika-Zeitoun D.
europepmc   +1 more source

Review of Prognosis Approaches Applied to Power SiC MOSFETs for Health State and Remaining Useful Life Prediction. [PDF]

Entropy (Basel)
Kumar S, Allard B, Hologne-Carpentier M, Clerc G, Auger F.   +4 more
europepmc   +1 more source

Longitudinal Patient-Reported Symptom Change Patterns and Prediction of Future Health-Related Quality of Life in Childhood Cancer Survivors: A Machine Learning Approach from the Childhood Cancer Survivor Study and the St. Jude Lifetime Cohort. [PDF]

Cancers (Basel)
Bagherzadeh-Khiabani F, Krull KR, Izumi S, Mirzaei S, Zheng T, Martinez JMM, Ness KK, Armstrong GT, Hudson MM, Robison LL, Yasui Y, Huang IC.   +11 more
europepmc   +1 more source

Predicting suicide attempts in a high-risk clinical cohort of adolescents using machine-learning. [PDF]

Eur Child Adolesc Psychiatry
Hertel C, Strahm N, Lerch S, Reichl C, Koenig J, Cavelti M, Kaess M.   +6 more
europepmc   +1 more source

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Toward Lifetime Learning-based Predictive

2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2021
Modeling system behavior plays a vital role in controlling systems and in monitoring systems health. Recently the machine learning-enabled modeling technology has become a powerful technique and tool for developing models for explaining, predicting, and describing system behaviors. In particular, the machine learning-enabled predictive modeling methods
Yang, Chunsheng, Guo, Yuhong, Yang, Yubin, Yang, Xiaohua   +3 more
openaire   +1 more source

On the prediction of Java object lifetimes

IEEE Transactions on Computers, 2006
Accurately predicting object lifetimes is important for improving memory management systems. Current garbage collectors make relatively coarse-grained predictions (e.g., "short-lived" versus "long-lived") and rely on application-independent heuristics related to the local characteristics of an allocation. This paper introduces a prediction method which
Hajime Inoue, Darko Stefanovic, Stephanie Forrest   +2 more
openaire   +1 more source