Artificial intelligence that can predict your every move, high-tech sensors, flashing coloured lights and an in-built charger. No, this isn't the latest sports car dreamed up by Silicon Valley wizards. It's the latest all-singing, all-dancing electric toothbrush – the Oral-B Genius X – which uses the same technology as that behind driverless vehicles and robots that diagnose diseases. The gadget can give users a new insight into their brushing habits, even down to the pressure applied on each tooth, makers claim. Oh, and it costs an eye-watering £340.
We introduce a Bayesian nonparametric regression model for data with multiway (tensor) structure, motivated by an application to periodontal disease (PD) data. Our outcome is the number of diseased sites measured over four different tooth types for each subject, with subject-specific covariates available as predictors. The outcomes are not well-characterized by simple parametric models, so we use a nonparametric approach with a binomial likelihood wherein the latent probabilities are drawn from a mixture with an arbitrary number of components, analogous to a Dirichlet Process (DP). We use a flexible probit stick-breaking formulation for the component weights that allows for covariate dependence and clustering structure in the outcomes. The parameter space for this model is large and multiway: patients $\times$ tooth types $\times$ covariates $\times$ components. We reduce its effective dimensionality, and account for the multiway structure, via low-rank assumptions. We illustrate how this can improve performance, and simplify interpretation, while still providing sufficient flexibility. We describe a general and efficient Gibbs sampling algorithm for posterior computation. The resulting fit to the PD data outperforms competitors, and is interpretable and well-calibrated. An interactive visual of the predictive model is available at http://ericfrazerlock.com/toothdata/ToothDisplay.html , and the code is available at https://github.com/lockEF/NonparametricMultiway .
Imaging fluorescent disease biomarkers in tissues and skin is a non-invasive method to screen for health conditions. We report an automated process that combines intraoral fluorescent porphyrin biomarker imaging, clinical examinations and machine learning for correlation of systemic health conditions with periodontal disease. 1215 intraoral fluorescent images, from 284 consenting adults aged 18-90, were analyzed using a machine learning classifier that can segment periodontal inflammation. The classifier achieved an AUC of 0.677 with precision and recall of 0.271 and 0.429, respectively, indicating a learned association between disease signatures in collected images. Periodontal diseases were more prevalent among males (p=0.0012) and older subjects (p=0.0224) in the screened population. Physicians independently examined the collected images, assigning localized modified gingival indices (MGIs). MGIs and periodontal disease were then cross-correlated with responses to a medical history questionnaire, blood pressure and body mass index measurements, and optic nerve, tympanic membrane, neurological, and cardiac rhythm imaging examinations. Gingivitis and early periodontal disease were associated with subjects diagnosed with optic nerve abnormalities (p <0.0001) in their retinal scans. We also report significant co-occurrences of periodontal disease in subjects reporting swollen joints (p=0.0422) and a family history of eye disease (p=0.0337). These results indicate cross-correlation of poor periodontal health with systemic health outcomes and stress the importance of oral health screenings at the primary care level. Our screening process and analysis method, using images and machine learning, can be generalized for automated diagnoses and systemic health screenings for other diseases.
Artificially intelligent software has found the next industry to potentially, as the kids say, disrupt – dentistry. A team of researchers from the University of California, Berkeley and Glidewell Dental Lab have built a generative adversarial network (GAN) to automatically generate new designs of dental crowns. GANs have been pretty trendy since 2014. There are hundreds of various acronyms for different GAN models like ABC-GAN, CatGAN, DiscoGAN, MAD-GAN, S2GAN, and so and so forth. All of them are made up of a generator and discriminator network duelling against each other.
Artificially intelligent software has found the next industry to potentially, as the kids say, disrupt – dentistry. A team of researchers from the University of California, Berkeley and Glidewell Dental Lab have built a general adversarial network (GAN) to automatically generate new designs of dental crowns. GANs have been pretty trendy since 2014. There are hundreds of various acronyms for different GAN models like ABC-GAN, CatGAN, DiscoGAN, MAD-GAN, S2GAN, and so and so forth. All of them are made up of a generator and discriminator network duelling against each other.
Vlocity, Inc., a cloud software company, announced the launch of automated claims features in their apps. The launch includes end-to-end management of property and casualty (P&C) insurance claims for policyholders, agents and claims handlers, and enables dynamic, digital claims interactions from any device. New features include peril-driven adjudication and an adjuster workbench that enhance a carrier's ability to run their entire business on Salesforce. Carriers can download pre-configured claims processes from Vlocity's Insurance Process Library and leverage a modern, optimized user experience. Carriers, if they prefer, can create a completely new experience from scratch in a code-free environment using Vlocity's intuitive design interface.
AI is going everywhere – into space, inside the human body and now, into your mouth. Ara, the world's first AI-capable toothbrush will actually teach you how to brush your teeth better. If you're a dentist, you'll probably get to keep your day job. Ara, from Kolibree, a French oral care company with offices in France and the United States, connects with an app on your smartphone to transmit data about your brushing habits. It will know exactly how you brush and whether or not it's good enough to keep dental problems at bay.
As if visiting the dentist wasn't scary enough, Orange County health officials are alerting parents to an outbreak of oral infections that appear linked to a children's dental office in Anaheim. At least one case of a Mycobacterial abscessus infection has been confirmed in a patient who visited the Children's Dental Group, in the 2100 block of East Lincoln Avenue in Anaheim, according to the OC Health Care Agency. The infection was detected after the child underwent a pulpotomy procedure to remove or treat an infected tooth, health officials said. The healthcare agency received multiple reports last week of children who had developed infections after undergoing the same procedure at the office. Eight children showed signs of "slowly progressive oral cellulitis" with dental abscesses and/or respiratory infections, officials said.