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1

Reduction of SPECT acquisition time using deep learning: A phantom study
Pribanić, Ivan ; Simić, Srđan Daniel ; Tanković, Nikola ; et al.
In Physica Medica July 2023 111

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2

Neural Networks for Predicting and Classifying Antimicrobial Resistance Sequences in Porphyromonas gingivalis
Yadalam, Pradeep Kumar ; Anegundi, Raghavendra Vamsi ; Natarajan, Prabhu Manickam ; et al.
In International Dental Journal October 2025 75(5)

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3

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions
Fu, Sunyang ; Jia, Heling ; Vassilaki, Maria ; et al.
In Journal of Biomedical Informatics April 2024 152

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4

Accelerated brain age in Moyamoya disease patients: a deep learning approach and correlation with disease severity.
Li, Wenjie ; Chen, Suhua ; Chen, Xin ; et al.
Frontiers in Neuroscience; 2025, p1-7, 7p

MOYAMOYA disease DEEP learning THERAPEUTICS BIOMARKERS COGNITIVE aging MAGNETIC resonance imagi... …
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5

تشخیص و شمارش خودکار کاکل های ذرت با استفاده از آشکارساز مبتنی بر یادگیری عمیق
شهرزاد فلاحت نژاد ماهانی ; اعظم کرمی
Journal of Agricultural Machinery. 2023, Vol. 13 Issue 2, p175-194. 20p.

CONVOLUTIONAL neural net... AGRICULTURAL drones OBJECT recognition (Comp... STANDARD deviations DRONE aircraft
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6

The Deep Learning with PyTorch Workshop
Saleh, Hyatt ; Saleh, Hyatt ; Saleh, Hyatt ; et al.

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7

A Primer on Deep Learning for Causal Inference.
Koch, Bernard J. ; Sainburg, Tim ; Geraldo Bastías, Pablo ; et al.
Sociological Methods & Research. May2025, Vol. 54 Issue 2, p397-447. 51p.

Algorithms Artificial neural networ... Treatment effect heterog... Causal inference Deep learning
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8

MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning.
Liu, Yidan ; Zhou, Zhenhua ; Wang, Yuanjun
Journal of X-Ray Science & Technology. Jan2025, Vol. 33 Issue 1, p26-36. 11p.

COMPUTER-aided diagnosis SPINAL cord tumors MAGNETIC resonance imagi... SYMPTOMS DIAGNOSTIC imaging DEEP learning
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9

LyFormer based object detection in reel package X-ray images of semiconductor component
Park, Jinwoo ; Lee, Jaehyeong ; Jeong, Jongpil
In Journal of King Saud University - Computer and Information Sciences January 2024 36(1)

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10

Deep Learning with PyTorch Quick Start Guide
Julian, David ; Julian, David ; Julian, David ; et al.

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11

Image-based deep learning of finite element simulations for fast surrogate biomechanical organ deformations
Ziche Lorenz ; Lenzig Bjarne ; Bieck Richard ; et al.
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 528-531 (2022)

physics-informed network... finite element simulatio... liver deformation deep learning pytorch cnn …
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12

Deep Learning and Scientific Computing with R torch.
Chowdhry, Amit K
Journal of the Royal Statistical Society: Series A (Statistics in Society). Jan2025, Vol. 188 Issue 1, p339-339. 1p.

PROGRAMMING languages SCIENCE education SOFTWARE maintenance SCHOOL discipline SCIENTIFIC computing DEEP learning
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13

An Educational Graphical User Interface to Construct Convolutional Neural Networks for Teaching Artificial Intelligence in Radiology.
Jin H ; Wagner MW ; Ertl-Wagner B ; et al.
Publisher: SAGE Publications Country of Publication: United States NLM ID: 8812910 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1488-2361 (Electronic) Linking ISSN: 08465371 NLM ISO Abbreviation: Can Assoc Radiol J Subsets: MEDLINE

Humans Neural Networks, Compute... Radiography Machine Learning Artificial Intelligence Radiology methods
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14

Introduction to PyTorch
Introduction to Deep Learning for Engineers : Using Python and Google Cloud Platform. 2020, p11-15.

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15

Experimental classification of pipeline magnetic leakage defects based on mixed attention mechanism. (English)
ZHANG Luying ; BIAN Yuchen ; ZHOU Lijiao ; et al.
Experimental Technology & Management; Jan2024, Vol. 41 Issue 1, p100-107, 8p

MAGNETIC flux leakage LEAK detection PETROLEUM pipelines DEEP learning SELENOPROTEINS MAGNETIC cores
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16

Machine learning for Earth sciences: using Python to solve geological problems: by Maurizio Petrelli, Switzerland AG, Springer Nature, 2023, xvi+209 pp., 352 figures, 61 table, €79.99 (Hardcover Book), ISBN: 9783031351136.
Oktavia Suhyani, Neli
International Geology Review. Jun2025, Vol. 67 Issue 12, p1635-1636. 2p.

LASER ablation inductive... DEEP learning MACHINE learning ARTIFICIAL intelligence SUPERVISED learning DISTRIBUTED computing …
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17

Automatic assessment of nailfold capillaroscopy software: a pilot study
Olga Elżbieta Brzezińska ; Krzysztof Andrzej Rychlicki-Kicior ; Joanna Samanta Makowska
Rheumatology, Vol 62, Iss 5, Pp 346-350 (2024)

microangiopathy capillaroscopy deep learning artificial intelligence Medicine
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18

An overview on deep learning-based approximation methods for partial differential equations
Beck, Christian ; Hutzenthaler, Martin ; Jentzen, Arnulf ; et al.
Discrete Contin. Dyn. Syst. Ser. B 28 (2023), no. 6, 3697-3746

Mathematics - Numerical... Computer Science - Machi... 65M99 (Primary), 35-02,...
Report
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19

PyTorch Hyperparameter Tuning - A Tutorial for spotPython
Bartz-Beielstein, Thomas

Computer Science - Machi... Computer Science - Artif... Mathematics - Numerical... 68T07 A.1 B.8.0 …
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20

Fast, memory-efficient genomic interval tokenizers for modern machine learning
LeRoy, Nathan J. ; Campbell Jr, Donald R. ; Stadick, Seth ; et al.

Genomics Machine Learning
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