Company Filing History:
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1 out of 12 Years Active: 2023
Title: Ragda Abdalla Aslan: Innovator in Machine Learning for Maxillofacial Bone Lesions
Introduction
Ragda Abdalla Aslan is a notable inventor based in Jerusalem, Israel. He has made significant contributions to the field of machine learning, particularly in the detection and classification of maxillofacial bone lesions. His innovative approach combines advanced technology with medical imaging to enhance diagnostic capabilities.
Latest Patents
Ragda holds a patent for a groundbreaking method titled "Machine learning detection and classification of maxillofacial bone lesions in CBCT." This computer-implemented method involves receiving a plurality of Cone Beam Computed Tomography (CBCT) scans, which include a series of axial slices. The scans are associated with two subgroups of subjects: one with maxillofacial bone lesions and another without. The process includes applying a feature extraction operation to derive a set of features from the axial slices. During the training stage, a machine learning model is trained on a dataset that includes all extracted features and annotations indicating the boundaries of bone lesions. This results in a trained model capable of detecting and segmenting bone lesions in axial slices from CBCT scans. Ragda has 1 patent to his name.
Career Highlights
Throughout his career, Ragda has worked with esteemed organizations such as Hadasit Medical Research Services and Development Ltd. and the Jerusalem College of Technology. His work in these institutions has allowed him to apply his expertise in machine learning to real-world medical challenges.
Collaborations
Ragda has collaborated with talented individuals in his field, including Chen Nadler and Talia Yeshua, who have contributed to his research and development efforts.
Conclusion
Ragda Abdalla Aslan is a pioneering inventor whose work in machine learning and medical imaging is making a significant impact in the diagnosis of maxillofacial conditions. His innovative patent demonstrates the potential of technology to improve healthcare outcomes.