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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Efficiently merge the multiomic information of patients with their health records to provide more tailored care solutions. Implement specialized data repositories to facilitate extensive analyses and foster collaborative research initiatives on a population-wide scale. Expedite research processes by leveraging adaptable workflows and comprehensive computational tools. Ensure the safeguarding of patient privacy through adherence to HIPAA standards, complete with robust data access and logging mechanisms. AWS HealthOmics empowers healthcare and life science organizations, along with their software collaborators, to securely store, retrieve, and analyze diverse omics data, such as genomic and transcriptomic information, ultimately yielding valuable insights that enhance health outcomes and propel scientific advancements. Manage and evaluate omics data for extensive patient cohorts to discern how variations in omics relate to phenotypic expressions within the population. Develop consistent and accountable clinical multiomics workflows designed to minimize turnaround times while boosting efficiency. Seamlessly incorporate multiomic assessments into clinical trials aimed at evaluating new therapeutic candidates, thereby enhancing the overall drug development process. By harnessing these innovative approaches, organizations can ensure a deeper understanding of patient health and contribute to groundbreaking research findings.

Description

JADBio is an automated machine learning platform that uses JADBio's state-of-the art technology without any programming. It solves many open problems in machine-learning with its innovative algorithms. It is easy to use and can perform sophisticated and accurate machine learning analyses, even if you don't know any math, statistics or coding. It was specifically designed for life science data, particularly molecular data. It can handle the unique molecular data issues such as low sample sizes and high numbers of measured quantities, which could reach into the millions. It is essential for life scientists to identify the biomarkers and features that are predictive and important. They also need to know their roles and how they can help them understand the molecular mechanisms. Knowledge discovery is often more important that a predictive model. JADBio focuses on feature selection, and its interpretation.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
Amazon Web Services (AWS) Yes 

Integrations

AWS AI Services No 
Amazon Web Services (AWS) No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Basic plan is FREE. Researchers plan starts at $400/mo
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/healthomics/

Vendor Details

Company Name

JADBio

Founded

2019

Country

United States

Website

jadbio.com

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library Yes 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization Yes 

Predictive Analytics

AI / Machine Learning Yes 
Benchmarking No 
Data Blending No 
Data Mining No 
Demand Forecasting No 
For Education No 
For Healthcare Yes 
Modeling & Simulation No 
Sentiment Analysis No 

Qualitative Data Analysis

Annotations No 
Collaboration No 
Data Visualization Yes 
Media Analytics No 
Mixed Methods Research No 
Multi-Language No 
Qualitative Comparative Analysis Yes 
Quantitative Content Analysis No 
Sentiment Analysis No 
Statistical Analysis No 
Text Analytics No 
User Research Analysis Yes 

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