A systematic literature review of deep learning application in multiclass anomaly detection for chest medical imaging
B Pardamean, GN Elwirehardja… - 2023 6th International …, 2023 - ieeexplore.ieee.org
Medical imaging abnormality detection is challenging, but deep learning approaches have
shown promise. This paper reviews the current state of the art in deep learning approaches …
shown promise. This paper reviews the current state of the art in deep learning approaches …
Interval type-2 possibilistic fuzzy clustering noisy image segmentation algorithm with adaptive spatial constraints and local feature weighting & clustering weighting
T Wei, X Wang, J Wu, S Zhu - International Journal of Approximate …, 2023 - Elsevier
The interval type-2 possibilistic fuzzy C-means (IT2PFCM) algorithm is a popular data
clustering and image segmentation method. However, the algorithm fails to consider the …
clustering and image segmentation method. However, the algorithm fails to consider the …
[HTML][HTML] Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients
S Verma, G Magazzù, N Eftekhari, T Lou, A Gilhespy… - Cell Reports …, 2024 - cell.com
Deep-learning tools that extract prognostic factors derived from multi-omics data have
recently contributed to individualized predictions of survival outcomes. However, the limited …
recently contributed to individualized predictions of survival outcomes. However, the limited …
State-of-the-art deep learning method and its explainability for computerized tomography image segmentation
WK Cheung - Explainable AI in Healthcare, 2023 - taylorfrancis.com
Medical image segmentation is an important task for computer-aided diagnosis. It provides
information on the target structure for physicians to perform accurate diagnosis and …
information on the target structure for physicians to perform accurate diagnosis and …
Responsible Deep Learning for Software as a Medical Device
Tools, models and statistical methods for signal processing and medical image analysis and
training deep learning models to create research prototypes for eventual clinical …
training deep learning models to create research prototypes for eventual clinical …
[PDF][PDF] A Systematic Literature Review of Deep Learning Application in Multiclass Anomaly Detection for Chest Medical Imaging
GN Elwirehardja, B Pardamean, M Isnan - academia.edu
Medical imaging abnormality detection is challenging, but deep learning approaches have
shown promise. This paper reviews the current state of the art in deep learning approaches …
shown promise. This paper reviews the current state of the art in deep learning approaches …
PRATIK SHAH
P SHAH - pratiks.info
Tools, models and statistical methods for signal processing and medical image analysis and
training deep learning models to create research prototypes for eventual clinical …
training deep learning models to create research prototypes for eventual clinical …