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Automatic detection and classification of leukocytes using convolutional neural networks
Automatic detection and classification of leukocytes using convolutional neural networks
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Automatic detection and classification of leukocytes using convolutional neural networks

Zhao, Jianwei ; Zhang, Minshu ; Zhou, Zhenghua ; Chu, Jianjun ; Cao, Feilong

Medical & biological engineering & computing, 2017-08, Vol.55 (8), p.1287-1301 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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A new parameter tuning approach for enhanced motor imagery EEG signal classification
A new parameter tuning approach for enhanced motor imagery EEG signal classification
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A new parameter tuning approach for enhanced motor imagery EEG signal classification

Kumar, Shiu ; Sharma, Alok

Medical & biological engineering & computing, 2018-10, Vol.56 (10), p.1861-1874 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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3
1001 Ways to run AutoDock Vina for virtual screening
1001 Ways to run AutoDock Vina for virtual screening
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1001 Ways to run AutoDock Vina for virtual screening

Jaghoori, Mohammad Mahdi ; Bleijlevens, Boris ; Olabarriaga, Silvia D.

Journal of computer-aided molecular design, 2016-03, Vol.30 (3), p.237-249 [Periódico revisado por pares]

Cham: Springer International Publishing

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4
Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations
Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations
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Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations

Candefjord, Stefan ; Winges, Johan ; Malik, Ahzaz Ahmad ; Yu, Yinan ; Rylander, Thomas ; McKelvey, Tomas ; Fhager, Andreas ; Elam, Mikael ; Persson, Mikael

Medical & biological engineering & computing, 2017-08, Vol.55 (8), p.1177-1188 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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5
Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach
Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach
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Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach

Jain, Pankaj K. ; Gupta, Saurabh ; Bhavsar, Arnav ; Nigam, Aditya ; Sharma, Neeraj

Medical & biological engineering & computing, 2020-03, Vol.58 (3), p.471-482 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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6
Low-light image enhancement of high-speed endoscopic videos using a convolutional neural network
Low-light image enhancement of high-speed endoscopic videos using a convolutional neural network
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Low-light image enhancement of high-speed endoscopic videos using a convolutional neural network

Gómez, Pablo ; Semmler, Marion ; Schützenberger, Anne ; Bohr, Christopher ; Döllinger, Michael

Medical & biological engineering & computing, 2019-07, Vol.57 (7), p.1451-1463 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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7
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

Rajpurkar, Pranav ; Irvin, Jeremy ; Ball, Robyn L ; Zhu, Kaylie ; Yang, Brandon ; Mehta, Hershel ; Duan, Tony ; Ding, Daisy ; Bagul, Aarti ; Langlotz, Curtis P ; Patel, Bhavik N ; Yeom, Kristen W ; Shpanskaya, Katie ; Blankenberg, Francis G ; Seekins, Jayne ; Amrhein, Timothy J ; Mong, David A ; Halabi, Safwan S ; Zucker, Evan J ; Ng, Andrew Y ; Lungren, Matthew P Sheikh, Aziz

PLoS medicine, 2018-11, Vol.15 (11), p.e1002686-e1002686 [Periódico revisado por pares]

United States: Public Library of Science

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8
Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet
Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet
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Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

Bien, Nicholas ; Rajpurkar, Pranav ; Ball, Robyn L ; Irvin, Jeremy ; Park, Allison ; Jones, Erik ; Bereket, Michael ; Patel, Bhavik N ; Yeom, Kristen W ; Shpanskaya, Katie ; Halabi, Safwan ; Zucker, Evan ; Fanton, Gary ; Amanatullah, Derek F ; Beaulieu, Christopher F ; Riley, Geoffrey M ; Stewart, Russell J ; Blankenberg, Francis G ; Larson, David B ; Jones, Ricky H ; Langlotz, Curtis P ; Ng, Andrew Y ; Lungren, Matthew P Saria, Suchi

PLoS medicine, 2018-11, Vol.15 (11), p.e1002699-e1002699 [Periódico revisado por pares]

United States: Public Library of Science

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9
Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis
Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis
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Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis

Dobbe, J. G. G. ; Streekstra, G. J. ; Atasever, B. ; van Zijderveld, R. ; Ince, C.

Medical & biological engineering & computing, 2008-07, Vol.46 (7), p.659-670, Article 659 [Periódico revisado por pares]

Berlin/Heidelberg: Springer-Verlag

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10
Comparison of scapular kinematics from optical motion capture and inertial measurement units during a work-related and functional task protocol
Comparison of scapular kinematics from optical motion capture and inertial measurement units during a work-related and functional task protocol
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Comparison of scapular kinematics from optical motion capture and inertial measurement units during a work-related and functional task protocol

Friesen, Kenzie B. ; Sigurdson, Anya ; Lang, Angelica E.

Medical & biological engineering & computing, 2023-06, Vol.61 (6), p.1521-1531 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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