Titlebook: Machine Learning in Dentistry; Ching-Chang Ko,Dinggang Shen,Li Wang Book 2021 Springer Nature Switzerland AG 2021 Dental big data.Digital

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Mary Lanier Zaytoun Berne,Feng-Chang Lin,Yi Li,Tai-Hsien Wu,Esther Chien,Ching-Chang Kond practice over the years.Examines pros and cons of the impThis book discusses key aspects of life in schools and classrooms, and surveys the changes that have occurred over the years in educational  research, policy making and practice in these school and classroom settings. It not only examines c

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Si Chen,Te-Ju Wu,Tai-Hsien Wu,Matthew Pastewait,Anna Zheng,Li Wang,Xiaoyu Wang,Ching-Chang Konvolved in its inception in 1999 and ultimately became the Resource’s co-Director for nearly 15 years. How did my scientific journey lead me to this position? I started my career as a research scientist in 1980, following the traditional pattern of Ph.D. then post-doctoral positions, initially study

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Machine Learning for CBCT Segmentation of Craniomaxillofacial Bony StructuresCone-beam computed tomography (CBCT) is routinely used to this end, by annotating the CMF bones (i.e., maxilla and mandible) from the CBCT volume. However, due to the poor quality of CBCT images, e.g., various image artifacts and very low signal-to-noise ratio, segmentation of CMF bones is a very ch

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Segmenting Bones from Brain MRI via Generative Adversarial LearningUnfortunately. CT emits radiation and is not a safe imaging modality, especially for infant patients. Thus, there is a clinical need of using alternative safer modalities, e.g., magnetic resonance imaging (MRI), for those patient populations. Although MRI provides good image quality for soft tissue,

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Machine Learning for Facial Recognition in Orthodonticsagnosis and planning treatment in modern orthodontics. The observation of the cranio-facial morphology enables the detection of not only orthodontic or orthopedic problems (e.g., the size and positions of the maxilla and mandibles) but also genetic problems. Recent improvements in technologies with

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Machine/Deep Learning for Performing Orthodontic Diagnoses and Treatment Planningto improve the plan quality, researchers have attempted to develop such systems. Artificial intelligence (AI) attempts to reflect advanced human intelligence in machines, and efforts to develop AI systems have been made since the advent of computers. In the 1980s, an expert system that expressed exp

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Machine (Deep) Learning for Characterization of Craniofacial Variations structure can reveal potential disorders that affect the patient’s quality of life. In recent years, the preferred method for diagnosis and treatment of patients with craniofacial disorders has been using Cone Beam Computed Tomography (CBCT) imaging accompanied by manual segmentation to produce a 3