We Design and Develop Innovative Technology for Healthcare Providers

HealthIT | HealthTech | MedTech | mHealth | Telemedicine / Telehealth

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HubBucket Project Directory ("HubDirectory")

HubDirectory list all of the HubBucket HealthIT, HealthTech, MedTech, mHealth, Telemedicine/Telehealth technology, Medical Research technology, etc. projects, coupled with their related information, resources, etc.

  • To learn more about the HubBucket Healthcare Technology projects, please visit our Project Directory.
  • Each of the HubBucket Healthcare Technology projects listed in the HubDirectory includes a code repository, and additional information.
  • We use a variety of Version Control repositories and Code Version Control tools.

HubBucket Registry ("HubRegistry)

HubBucket Registry ("HubRegistry") is a Package Manager Pipeline for:

HubBucket Discovery ("HubDiscovery")

HubBucket Discovery ("HubDiscovery") is an Intelligent Health Information Technology - HealthIT Platform that consists of Open Source software and technology that encapsulates:

  • Machine Learning Models, Algorithms, and Frameworks
  • Deep Learning Models, Algorithms, and Frameworks
  • Continuous Integration - CI tools
  • Continuous Delivery - CD tools
  • Site Reliability Engineering - SRE tools that support SRE methodologies
  • Development and Operations - DevOps tools that support DevOps methodologies

HubFabric - HubBucket Artificial Intelligence – AI HyperConverged Infrastructure for Health Information Technology - HealthIT/HIT

HubFabric is also a suite of HealthIT products and services, consisting of:

  • HubFabricONE - HubBucket Fabric ONE Cloud-based Service Mesh Technology
  • HubFabricVM - HubBucket Fabric Virtualization Appliance Technology
  • HubFabricAPIs - HubBucket Fabric Application Programming Interface - APIs
  • HubFlow - HubBucket Flow - Automated Machine Learning - AutoML Data Lake Management Technology
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HubBucket designs and develops innovative technology for Healthcare Providers.

Our healthcare technology development includes:

  • Health Information Technology - HealthIT / HIT
  • Health Technology - HealthTech
  • Medical Technology - MedTech
  • Mobile Health Technology - mHealth
  • Wearable Health Technology and Sensors
  • Telemedicine / Telehealth
  • Internet of Medical Things - IoMT
  • Blockchain Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Medical Imaging Technology
  • Technology for Medical / Medicine Research
  • Clinical Informatics, Bioinformatics
  • Healthcare Analytics Applications Healthcare
  • Descriptive Analytics for Healthcare
  • Diagnostic Analytics for Healthcare
  • Predictive Analytics for Healthcare
  • Prescriptive Analytics for Healthcare
  • Real-Time Data Analysis Platform and Applications
  • Big Data Healthcare Applications Real-Time
  • Healthcare Data Streaming Technology
  • Medical Digital Twin Technology
  • Dark Data Management Healthcare Platform
  • Healthcare Exchange Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Cloud-based Healthcare Applications
  • Edge Computing Healthcare Technology and Applications
  • Healthcare Application Programming Interface - APIs
  • API Gateway Technology for Healthcare
  • Serverless Technology for Healthcare
  • Mesh Technology for Healthcare
  • Healthcare Digital Repository Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Healthcare Digital Archive Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Healthcare Data Catalog Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Healthcare Data Discovery Technology for Electronic Health Records - EHR, Electronic Medical Records - EMR, etc.
  • Healthcare Data Lake Automation and Orchestration Technology

Our healthcare technology is integrated with one or more of the following:

  • Artificial Intelligence - AI
  • Machine Learning models and algorithms
  • Deep Learning models and algorithms
  • Automated Machine Learning - AutoML
  • Computer Vision / Machine Vision
  • Natural Language Processing - NLP / NLProc
  • Natural Language Understanding - NLU
  • Neural Machine Translation - NMT / MT

Open Source

We use Open Source technology from various organizations to build our health technology. Please see our Open Source page to learn more.

Cloud Computing

Furthermore, we use a wide variety of Cloud Service Providers - CSPs Cloud-based services to operate and manage HubBucket, coupled with designing and developing our health technology products and services. Please see our Cloud Computing page to learn more.

 

Important note on Artificial Intelligence - AI, Machine Learning, Deep Learning and Algorithm Bias:

  • Our Data Scientists, Engineers, Developers, etc. take steps to ensure that all of the Machine Learning and Deep Learning models and algorithms are constructed without Racial and Gender Bias.
  • Our Data Scientists, Engineers, Developers, etc. take steps to ensure that all Racial and Gender Bias in Data used to train our Machine Learning and Deep Learning models and algorithms is removed before any Machine Learning and Deep Learning training begins.

HubBucket, Inc. ("HubBucket") adheres to all United States (U.S.) federal, New York State (NYS), California (state), and international Data Protection Laws, Regulations and Standards, which includes the European Union (EU) Data Protection Laws.


HubBucket is in compliance with the following laws, regulations, and standards, in addition to other U.S. Federal Laws:

Additional Information: https://www.healthit.gov/topic/laws-regulation-and-policy/health-it-legislation


Data Protection Law

Data Protection Law deals with the security of the electronic transmission of personal data. As of yet, the United States does not have any centralized, formal legislation at the federal level regarding this issue, but does insure the privacy and protection of data through the United States Privacy Act, the Safe Harbor Act and the Health Insurance Portability and Accountability Act.

U.S. Sectoral Approach

The United States follows what is referred to as a 'sectoral' approach to data protection legislation. Under this approach, the laws of data protection and privacy rely on a combination of legislation, regulation, and self-regulation rather than governmental interference alone. Since the Clinton administration, the U.S. has followed a policy geared toward allowing the private sector to lead the way in data protection. This means that companies should implement their own policies, develop their own technology, and individuals should self-regulate to prevent the dissemination of their private data. Pursuant to this policy, the US has not yet developed a single, federal data protection law.

European Union - EU Data Protection Laws

The European Union, on the other hand, has a unified data protection law called the Data Protection Directive. The EU's Data Protection Directive regulates the processing of personal data within the European Union and is an important component of the EU's privacy and human rights law. However, recognizing the need to modify this law to deal with globalization and technological developments, the European Union prepared a draft European General Data Protection Regulation that will supersede the Data Protection Directive, which is targeted for adoption in 2014 and to become effective in 2016. The existing Data Protection Directive, in simplest terms, asserts that personal data should not be processed at all, but if it is, it must fall within certain categories of transparency, legitimate purpose, and proportionality. The proposed law would expand the data protection regime currently in place to cover all international companies doing business in the EU.

The United States of America - U.S.A Ad Hoc Privacy Laws

Under the U.S. Sectoral approach, however, privacy legislation tends to be sparse and only adopted on an ad hoc basis, with legislation arising when circumstances require. These laws usually only apply to situations in which individuals would not be able to control the use of their data through self-regulations. Examples include the Video Privacy Protection Act of 1988, the Cable Television Protection and Competition Act of 1992, and the Fair Credit Reporting Act.

The United States of America - U.S.A Privacy Law Traditions

The reasoning behind the U.S. approach to privacy laws has as much to do with American laissez-faire economics as with its legal tradition. For example, while the U.S. has prized its right to free speech so dearly that the very first amendment to the U.S. Constitution protects it explicitly, the Constitution does not have an explicit right to privacy. The U.S. Supreme Court has found a right to privacy implied by the terms of other portions of the Constitution, and many states have explicit privacy rights in their state constitutions, but on a federal level, there is no express constitutional guarantee to privacy. As a result, there is similarly no constitutional framework upon which to build a single data privacy act, making the ad hoc approach much more compatible with the American system of government

For more information on data protection laws, please refer to the materials found below on this page. Moreover, should you need the assistance of an attorney to protect your rights as related to a data protection issue, whether as a person or entity that acquires and uses this data or as one who is afraid of the misuse of your personal information, you can find a list of attorneys in your area by visiting our Law Firms page.


Source: https://www.hg.org/data-protection.html