| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A deep learning-based fully automatic and clinical-ready framework for regional myocardial segmentation and myocardial ischemia evaluation
|
An, Mujun
|
|
|
61 |
6 |
p. 1507-1520
|
artikel
|
| 2 |
Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis—Review of literature and in vitro case study
|
Ampadi Ramachandran, Remya
|
|
|
61 |
6 |
p. 1239-1255
|
artikel
|
| 3 |
A spatiotemporal analysis of the left coronary artery biomechanics using fluid–structure interaction models
|
Fandaros, Marina
|
|
|
61 |
6 |
p. 1533-1548
|
artikel
|
| 4 |
A survey of machine learning-based methods for COVID-19 medical image analysis
|
Sailunaz, Kashfia
|
|
|
61 |
6 |
p. 1257-1297
|
artikel
|
| 5 |
Cardiorespiratory coupling in mechanically ventilated patients studied via synchrogram analysis
|
Ottolina, Davide
|
|
|
61 |
6 |
p. 1329-1341
|
artikel
|
| 6 |
CML-Cardio: a cascade machine learning model to predict cardiovascular disease risk as a primary prevention strategy
|
Oliveira, Bruno Alberto Soares
|
|
|
61 |
6 |
p. 1409-1425
|
artikel
|
| 7 |
Colorectal cancer lymph node metastasis prediction with weakly supervised transformer-based multi-instance learning
|
Tan, Luxin
|
|
|
61 |
6 |
p. 1565-1580
|
artikel
|
| 8 |
Comparison of scapular kinematics from optical motion capture and inertial measurement units during a work-related and functional task protocol
|
Friesen, Kenzie B.
|
|
|
61 |
6 |
p. 1521-1531
|
artikel
|
| 9 |
Correction to: Customizable tubular model for n‑furcating blood vessels and its application to 3D reconstruction of the cerebrovascular system
|
Chlebiej, Michal
|
|
|
61 |
6 |
p. 1363
|
artikel
|
| 10 |
Customizable tubular model for n-furcating blood vessels and its application to 3D reconstruction of the cerebrovascular system
|
Chlebiej, Michal
|
|
|
61 |
6 |
p. 1343-1361
|
artikel
|
| 11 |
Design and evaluation of vascular interventional robot system for complex coronary artery lesions
|
Yu, Haoyang
|
|
|
61 |
6 |
p. 1365-1380
|
artikel
|
| 12 |
Does preclinical analysis based on static loading underestimate post-surgery stem micromotion in THA as opposed to dynamic gait loading?
|
Vio War, Adeline S.
|
|
|
61 |
6 |
p. 1473-1488
|
artikel
|
| 13 |
Effects of bilateral sagittal split ramus osteotomy and bimaxillary osteotomies on stress distribution of temporomandibular joints in patients with maxillofacial deformity under asymmetric occlusions
|
Luo, Haotian
|
|
|
61 |
6 |
p. 1427-1437
|
artikel
|
| 14 |
Few-shot learning using explainable Siamese twin network for the automated classification of blood cells
|
Tummala, Sudhakar
|
|
|
61 |
6 |
p. 1549-1563
|
artikel
|
| 15 |
Influence of aortic valve morphology on vortical structures and wall shear stress
|
Jonnagiri, Raghuvir
|
|
|
61 |
6 |
p. 1489-1506
|
artikel
|
| 16 |
Multi-band spatial feature extraction and classification for motor imaging EEG signals based on OSFBCSP-GAO-SVM model
|
Shang, Yong
|
|
|
61 |
6 |
p. 1581-1602
|
artikel
|
| 17 |
Path planning for percutaneous lung biopsy based on the loose-Pareto and adaptive heptagonal optimization method
|
Liu, Qi
|
|
|
61 |
6 |
p. 1449-1472
|
artikel
|
| 18 |
PneuNet: deep learning for COVID-19 pneumonia diagnosis on chest X-ray image analysis using Vision Transformer
|
Wang, Tianmu
|
|
|
61 |
6 |
p. 1395-1408
|
artikel
|
| 19 |
The mechanical behavior of bovine spinal cord white matter under various strain rate conditions: tensile testing and visco-hyperelastic constitutive modeling
|
Jiang, Fei
|
|
|
61 |
6 |
p. 1381-1394
|
artikel
|
| 20 |
The role of the joint capsule in the stability of the elbow joint
|
Wang, Fang
|
|
|
61 |
6 |
p. 1439-1448
|
artikel
|
| 21 |
Toward a robust swallowing detection for an implantable active artificial larynx: a survey
|
Mialland, Adrien
|
|
|
61 |
6 |
p. 1299-1327
|
artikel
|
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