North America Healthcare Application Programming Interface (API) Market Report 2020 – Press Release

Dublin, Oct. 02, 2020 (GLOBE NEWSWIRE) — The “North America Healthcare API Market by Services, by End User, by Deployment, by Country, Industry Analysis and Forecast, 2020 – 2026” report has been added to ResearchAndMarkets.com’s offering.

The North America Healthcare API Market is expected to witness market growth of 5.6% CAGR during the forecast period (2020-2026).

Patient-centric healthcare is a developing value-based model for healthcare services, which has brought about an improvement in care quality, better results, and more prominent patient satisfaction. Developing focus on patient-centric healthcare delivery by means of application programming interfaces (APIs) has been noted over a few past years and the rise of a large group of services, for example, wearable medical gadgets and remote patient monitoring have prodded the demand for healthcare API solutions.

Expanding adoption of Application Programming Interfaces (API) coordinated Electronic Health Records (EHRs) that give straightforwardness and simplicity of healthcare data availability is driving the market development. Besides, improved patient results expanded patient satisfaction, and advancement in the care quality is driving the market expansion. Besides, expanding the requirement for healthcare integration is driving interest.

Incorporation of new work processes between the providers and the payers, the applications which can get to information from EHRs, wearables, and their services, consistent progress of care are some of the important factors expanding the adoption of healthcare API. Inside normalization for different items or work processes will help to effortlessly access the patient’s information.

Key Topics Covered:

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.5 Methodology for the research

Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.2 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints

Chapter 3. Competition Analysis – Global
3.1 Cardinal Matrix
3.2 Recent Industry

Telecom Application Programming Interface (API) Platform Market Emerging Trends, Revenue Estimation, Global Size and Forecast Report to 2025

The MarketWatch News Department was not involved in the creation of this content.

Sep 29, 2020 (Heraldkeepers) —
The global telecom API platform market is expected to exceed more than US$ 490 bn by 2024 at a CAGR of 23.5% between 2018 and 2024.

The telecom API platform market is segmented on the lines of its telecom operator and module. Under telecom operator segmentation it covers T1 players, T2 players and T3 players. The telecom API platform market is segmented on the lines of its module like set-up, monetization and pricing model, operator share and vendor share. The telecom API platform market is geographic segmentation covers various regions such as North America, Europe, Asia Pacific, Latin America, Middle East and Africa. Each geography market is further segmented to provide market revenue for select countries such as the U.S., Canada, U.K. Germany, China, Japan, India, Brazil, and GCC countries.

Browse Full Report here: https://www.marketresearchengine.com/reportdetails/global-telecom-api-platform-market

The report covers detailed competitive outlook including the market share and company profiles of the key participants operating in the global market. Key players profiled in the report include S.A., Aepona Ltd., Apigee Corp., Huawei Technologies Co. Ltd., Oracle Corp., Hewlett-Packard Development Co., LM Ericsson, Tropo, Inc., Axway Software S.A., and ZTE Soft Technology Co., Ltd.. Company profile includes assign such as company summary, financial summary, business strategy and planning, SWOT analysis and current developments.

API that is application programming interface is a key element in a many business foundation which presents revenue creation services through association with outdoor partners. API acts as middleware software which forms interface among resources and applications in the device. It presents expertise with services and tools for the reason of API design, management and reporting for the best functioning of API programs to increase business revenue. It plays fundamental role for

New Brain-Computer Interface Transforms Thoughts to Images

TheDigitalArtist/Pixabay

Source: TheDigitalArtist/Pixabay

Achieving the next level of brain-computer interface (BCI) advancement, researchers at the University of Helsinki used artificial intelligence (AI) to create a system that uses signals from the brain to generate novel images of what the user is thinking and published the results earlier this month in Scientific Reports.

“To the best of our knowledge, this is the first study to use neural activity to adapt a generative computer model and produce new information matching a human operator’s intention,” wrote the Finnish team of researchers.

The brain-computer interface industry holds the promise of innovating future neuroprosthetic medical and health care treatments. Examples of BCI companies led by pioneering entrepreneurs include Bryan Johnson’s Kernel and Elon Musk’s Neuralink.  

Studies to date on brain-computer interfaces have demonstrated the ability to execute mostly limited, pre-established actions such as two-dimensional cursor movement on a computer screen or typing a specific letter of the alphabet. The typical solution uses a computer system to interpret brain-signals linked with stimuli to model mental states. Seeking to create a more flexible, adaptable system, the researchers created an artificial system that can imagine and output what a person is visualizing based on brain signals. The researchers report that their neuroadaptive generative modeling approach is “a new paradigm that may strongly impact experimental psychology and cognitive neuroscience.”

The University of Helsinki researchers used a combination of a generative neural network with neuroadaptive brain interfacing to create a new BCI paradigm. Neuroadaptive generative modeling is the estimation of a person’s intentions via adapting a generative model to neural activity. To expand capabilities and not be limited to pre-defined categories, the researchers based the solution on a generative adversarial network (GAN) to generate novel information from a latent representation of an input space.

Generative adversarial networks are a relatively recent