A5087866008- Radiomics and Machine Learning in Medical Imaging
- Scientific Computing and Data Management
- Artificial Intelligence in Healthcare and Education
- Distributed and Parallel Computing Systems
- Medical Imaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Computational Physics and Python Applications
- Advanced Neural Network Applications
- AI in cancer detection
- Microtubule and mitosis dynamics
- Biomedical Ethics and Regulation
- Image and Object Detection Techniques
- Craniofacial Disorders and Treatments
- Colorectal Cancer Treatments and Studies
- Ocular Disorders and Treatments
- Biomedical Text Mining and Ontologies
- Genetic and Kidney Cyst Diseases
- Cloud Computing and Remote Desktop Technologies
- Medical Image Segmentation Techniques
- Cleft Lip and Palate Research
- Chromosomal and Genetic Variations
- Artificial Intelligence in Healthcare
- Corneal Surgery and Treatments
- Semantic Web and Ontologies
- Congenital Anomalies and Fetal Surgery
Heidelberg University
2016-2021
German Cancer Research Center
2014-2021
Deutschen Konsortium für Translationale Krebsforschung
2020-2021
DKFZ-ZMBH Alliance
2014-2018
Délégation Paris 6
1982
National Cancer Institute
1951
American Society of Plastic Surgeons
1951
Duke University Hospital
1951
PURPOSE Image analysis is one of the most promising applications artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment diseases. Although scientific advances this area critically depend on accessibility large-volume high-quality data, sharing data between institutions faces various ethical legal constraints as well organizational technical obstacles. METHODS The Joint Imaging Platform (JIP) German Cancer Consortium (DKTK) addresses these...
Accurate segmentations in medical images are the foundations for various clinical applications. Advances machine learning-based techniques show great potential automatic image segmentation, but these usually require a huge amount of accurately annotated reference training. The guiding hypothesis this paper was that crowd-algorithm collaboration could evolve as key technique large-scale data annotation. As an initial step toward goal, we evaluated performance untrained individuals to detect...
Although most animal cells contain centrosomes, consisting of a pair centrioles, their precise contribution to cell division and embryonic development is unclear. Genetic ablation STIL, an essential component the centriole replication machinery in mammalian cells, causes lethality mice around mid gestation associated with defective Hedgehog signaling. Here, we describe, by focused ion beam scanning electron microscopy, that STIL−/− mouse embryos do not centrioles or primary cilia, suggesting...
PICKRELL, K. L. M.D.; EDWARDS, B. F. BROADBENT, T. R. M.D.†; WILDE, N. J. METZGER, M.D. Author Information
In the surgical domain, individual clinical experience, which is derived in large part from past cases, plays an important role treatment decision process. Simultaneously surgeon has to keep track of a amount data, emerging number heterogeneous systems during all phases treatment. This complemented with constantly growing knowledge studies and literature. To recall this vast information at right moment poses challenge that should be supported by adequate technology. While many tools projects...
Although digital and data-based technologies are widespread in various industries the context of Industry 4.0, use smart connected devices health care is still its infancy. Innovative solutions for medical environment affected by difficult access to device data high barriers market entry because proprietary systems.In proof-of-concept project OP 4.1, we show business viability connecting augmenting through software add-ons giving companies a technical commercial platform development,...
LIP Pacing AERmin (mV) 0.9+0.5 (0.2 -2.1) ARTmax 0.1+0.1 (O.l-0.3)SAR min 7.6+4.3(1.7 -18.0)Analyzed results: mean + SD (range) BP 2.5+1.7 (0.5 -7.4) 2.5+2.3 -7.5) 1.7+1.3(0.4 -5.2) Conclusion: Adequate automatic atria1 pacing threshold determination based on AER detection is reliable with unipolar pacing.The lower SUCCESS rate bipolar can be explained by the use of a common atrial ring electrode in pacing/detection circuit.I
<sec> <title>BACKGROUND</title> Although digital and data-based technologies are widespread in various industries the context of Industry 4.0, use smart connected devices health care is still its infancy. Innovative solutions for medical environment affected by difficult access to device data high barriers market entry because proprietary systems. </sec> <title>OBJECTIVE</title> In proof-of-concept project OP 4.1, we show business viability connecting augmenting through software add-ons...