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Fovea prediction model in VR

• Authors : Giunchi, Daniele; Bovo, Riccardo; Bhatia, Nitesh

Subjects: Computer Science; Artificial Intelligence; CyberneticsOrlando; FL; USA

• Source: IEEE Conference on Virtual Reality and 3D User Interfaces (VR) ; 870 ; 869

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Uncertainty estimation with prediction-error circuits

• Authors : Hertäg, Loreen; Wilmes, Katharina A; Clopath, Claudia

Subjects: Uncertainty; Models; NeurologicalEngland

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Phyre2.2: a community resource for template-based protein structure prediction

• Authors : Powell, Harold R; Islam, Suhail A; David, Alessia

Subjects: Protein structure predictionPhyre2.2Homology modelingBioinformatics

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Risk-prediction models and clinical challenges in the ROCkeTS study – authors' reply

• Authors : Sundar, Sudha; Davenport, Clare; Scandrett, Katie

Subjects: 1112 Oncology and Carcinogenesis; Oncology & CarcinogenesisEngland

• Source: e5 ; e4

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Prediction of seismic demands for ancillary elements in vertically irregular steel frames

• Authors : Ding, X; Liapopoulou, M; Elghazouli, AY

• Source: 109418.

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Assessing uncertainty and heterogeneity in machine learning-based spatiotemporal ozone prediction in Beijing-Tianjin- Hebei region in China

• Authors : Cheng, Meiling; Fang, Fangxin; Navon, Ionel Michael

Subjects: Generative adversarial network; Machine learning; Ozone concentration predictionNetherlands

• Source: 13 ; 1

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Prediction-error neurons in circuits with multiple neuron types: formation, refinement, and functional implications.

• Authors : Hertäg, L; Clopath, C;

Subjects: homeostatic plasticity; inhibitory interneurons; prediction-error neuronsUnited States

• Source: e2115699119

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EczemaPred: a computational framework for personalised prediction of eczema severity dynamics

• Authors : Hurault, G; Stalder; Mery ...

Subjects: Science & Technology; Life Sciences & Biomedicine; Allergy

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A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.

• Authors : Hindocha, S; Charlton, TG; Linton-Reid, K

Subjects: Early detection; Machine learning; Non-small cell lung cancer

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Is the SMART risk prediction model ready for real-world implementation? A validation study in a routine care setting of approximately 380 000 individuals

• Authors : McKay, AJ; Gunn, LH; Ference, BA

Subjects: Science & Technology; Life Sciences & Biomedicine; Cardiac & Cardiovascular SystemsEngland

• Source: 663 ; 654

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