“Machine Learning of Dental Images to Expedite Insurance Claim Approvals and Identify Insurance Fraud” in Patent Application Approval Process (USPTO 20220005588): Patent Application

2022 JAN 26 (NewsRx) -- By a News Reporter-Staff News Editor at Daily Veterinary News -- A patent application by the inventors Cambria, Andrea (New York, NY, US); Ricci, Richard (New York, NY, US), filed on January 29, 2021, was made available online on January 6, 2022, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application has not been assigned to a company or institution.

The following quote was obtained by the news editors from the background information supplied by the inventors: “Digital dental images have revolutionized the entire dental field. Today, digital radiography is common place in the vast majority of dental offices. Doctors, hygienists and staff are ubiquitously trained in the taking of digital dental images. Digital dental images have led to huge improvements in patient diagnosis and treatment options. Digital dental x-rays are processed vastly faster than traditional film dental x-rays. In addition to this, the patient’s radiation exposure is significantly less with digital dental x-rays. Patient dental image management service(s) provide a wide variety of applications ranging from offsite image hosting, dental image attachments to insurance claims, dental laboratory scans, x-ray to graphic based charting and dental charting by voice command.

“In 2014 52.3% of Americans reported visiting the dentist every 6 months. Statistically, everyone will need to have routine or emergency dental care in their lifetime. It is highly likely that each of these patients will require dental x-rays. Dental images, such as dental x-rays and digital dental images, offer a unique authentication of an individual and can be immensely useful for law enforcement to track and identify patients who may be persons of interest. Hence there is a need to develop this technology for national security purposes.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “The present invention and its embodiments relate to at least one of: deep learning, machine learning of dental images for national security utilizing e-commerce. Wherein e-commerce is the activity of transferring at least one of: a product, a good, a data, a currency, a discount, a software, an application, an advertisement, an image, an information, a service over a communication network. Wherein, a communication network is at least one of: a secure communication network, an encrypted communication network, the internet, an intranet, an extranet, an internet, an internet transaction service, an online transaction service, a mobile network, a wireless network, an online transaction processing (OLTP) service, an online analytical processing (OLAP), a transaction platform, an internet transaction platform. Wherein, national security is the security and defense of a nation state, including its citizens, economy, and institutions, which is regarded as a duty of government. The system may provide at least one of: deep learning, machine learning of a dental image for national security utilizing e-commerce. The system may include a microprocessor device. The microprocessor is configured to execute an instruction in any order. Further, the microprocessor is configured to omit an instruction in any order. Wherein an instruction is at least one of: a process, a match, an identify, a generate, a train, a provide, a transaction, an exchange, transfer, a buy, a sell. The microprocessor may be configured to receive dental images of at least one of: an e-commerce consumer, a person of interest from at least one of: an e-commerce provider, an e-commerce administrator, a machine learning entity, an e-commerce organization, a government entity, a law enforcement entity, a person of interest. The microprocessor may be configured to process dental images of at least one of: an e-commerce consumer, a person of interest from at least one of: an e-commerce provider, an e-commerce administrator, a machine learning entity, an e-commerce organization, a government entity, a law enforcement entity, a person of interest. An e-commerce consumer may be a person of interest. An example of a dental image e-commerce provider may include at least one of: a business entity, a business owner, an employer, a wholesaler, a retailer, a professional, a dentist, a dental hygienist, a dental professional, a physician, a health professional, a group, a veterinarian, a veterinarian professional, a research entity, a law enforcement entity, a public administration entity, a bioinformatics service, an insurance company, a cloud based storage service. Further, an e-commerce provider may be an expert in one or more of the following fields of dentistry: restorative, prosthodontics, periodontics, endodontics, oral surgery, pediodontics, radiology, pathology, tempro-mandibular joint (TMJ) specialist, orthodontist. An example of a dental image e-commerce consumer may include at least one of: a patient, an individual, a person of interest, a guardian, a group, an employee. An example of an e-commerce administrator may include at least one of: an administrator, an administrator entity, a law enforcement agency, a governing agency. An example of a person of interest may be at least one of: a terrorist, a violent criminal, a nonviolent criminal, a cybercrime criminal, a political criminal, a white collar criminal, an innocent person. Wherein, a terrorist may be at least one of: a terrorist, an assassin, an arms trader, a piracy, a smuggler, an arsonist, a hijacker. Wherein, a violent crime may include at least one of: a homicide, a kidnapper, a rapist, a sex assault, a sexual offender, a child sex offender, an arsonist, a domestic violence, a sex trafficker, a fugitive, a drug trafficker, an abducted child, a hate crime, a violent crime. Wherein, a nonviolent crime may be at least one of: a theft, a property crime, a racketeering crime, a gambling crime, a bribery crime, a prostitution crime, a missing person, a discrimination crime, a traffic crime, a failure to pay a child support, a failure to pay an alimony payment, a shoplifting, a non violent crime. Wherein, a cybercriminal may include at least one of: a cyberterrorist, a cyberwarefare, a cyberextortion, a cyber sex trafficking, an espionage, a ransomware, a malware, a data hacker, an identity theft, a computer crime. Wherein, a political crime may include at least one of: a treason, a sedition, a terrorism, an espionage, a religious crimes, an anti-Semite crime, a crime against a government. Wherein, a white collar crime may include at least one of: an insider trader, a ponzi scheme, an embezzler, an extortionist, a forgery, a nepotism, a tax evader, a briber, a fraud, a counterfeiter, a money laundering, a copyright infringement, a non violent crime.

“Next, the dental images for e-commerce may be processed with at least one of: deep learning, machine learning with a computer vision image class dataset and may further be processed with a large computer vision image class dataset. A computer vision image class may be matched to at least one of: an individual e-commerce consumer dataset, a larger e-commerce dataset. Both computer vision datasets and the e-commerce datasets may be merged and correlated with large datasets and provided to at least one of: an e-commerce provider, an e-commerce consumer, an e-commerce administrator, a machine learning entity, an e-commerce organization, a government entity, a law enforcement entity, a person of interest. The dental images for e-commerce may also be processed with at least one of: a deep learning computer vision object class dataset, a machine learning computer vision object class dataset. A computer vision object class from the deep learned and/or machine learned computer vision object class dataset may be matched to at least one of: an individual e-commerce consumer dataset, a larger e-commerce dataset. Both computer vision datasets and the e-commerce consumer dataset may be merged and correlated with large datasets and provided to at least one of: an e-commerce provider, an e-commerce consumer, an e-commerce administrator, a machine learning entity, an e-commerce organization, a government entity, a law enforcement entity, a person of interest. In addition, a cluster analysis of the e-commerce consumer dataset may be performed with a cluster dataset to produce correlated dental images for e-commerce. Furthermore, the correlated dental images for e-commerce may be provided to a machine learning entity to compile a diagnostic probability aid for at least one of: an e-commerce provider, an e-commerce consumer, an e-commerce administrator, a machine learning entity, an e-commerce organization, a government entity, a law enforcement entity, a person of interest.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“strong>”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent application, see: Cambria, Andrea; Ricci, Richard. Machine Learning of Dental Images to Expedite Insurance Claim Approvals and Identify Insurance Fraud. Filed January 29, 2021 and posted January 6, 2022. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220220005588%22.PGNR.&OS=DN/20220005588&RS=DN/20220005588

(Our reports deliver fact-based news of research and discoveries from around the world.)