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Artificial Intelligence

Global Machine Learning in Life Sciences Market Report to 2027 – Rising Chronic Diseases and Investments in the AI Health Sector is Driving Growth

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Dublin, Sept. 29, 2022 (GLOBE NEWSWIRE) — The “Global Markets for Machine Learning in the Life Sciences” report has been added to ResearchAndMarkets.com’s offering.

This report highlights the current and future market potential for machine learning in life sciences and provides a detailed analysis of the competitive environment, regulatory scenario, drivers, restraints, opportunities and trends in the market. The report also covers market projections from 2022 through 2027 and profiles key market players.

The publisher analyzes each technology in detail, determines major players and current market status, and presents forecasts of growth over the next five years. Scientific challenges and advances, including the latest trends, are highlighted. Government regulations, major collaborations, recent patents and factors affecting the industry from a global perspective are examined.

Key machine learning in life sciences technologies and products are analyzed to determine present and future market status, and growth is forecast from 2022 to 2027. An in-depth discussion of strategic alliances, industry structures, competitive dynamics, patents and market driving forces is also provided.

Artificial intelligence (AI) is a term used to identify a scientific field that covers the creation of machines (e.g., robots) as well as computer hardware and software aimed at reproducing wholly or in part the intelligent behavior of human beings. AI is considered a branch of cognitive computing, a term that refers to systems able to learn, reason and interact with humans. Cognitive computing is a combination of computer science and cognitive science.

ML algorithms are designed to perform tasks such data browsing, extracting information that is relevant to the scope of the task, discovering rules that govern the data, making decisions and predictions, and accomplishing specific instructions. As an example, ML is used in image recognition to identify the content of an image after the machine has been instructed to learn the differences among many different categories of images.

There are several types of ML algorithms, the most common of which are nearest neighbor, naive Bayes, decision trees, a priori algorithms, linear regression, case-based reasoning, hidden Markov models, support vector machines (SVMs), clustering, and artificial neural networks. Artificial neural networks (ANN) have achieved great popularity in recent years for high-level computing.

They are modeled to act similarly to the human brain. The most basic type of ANN is the feedforward network, which is formed by an input layer, a hidden layer and an output layer, with data moving in one direction from the input layer to the output layer, while being transformed in the hidden layer.

Report Includes

  • 32 data tables and 28 additional tables
  • A comprehensive overview and up-to-date analysis of the global markets for machine learning in life sciences industry
  • Analyses of the global market trends, with historic market revenue data for 2020 and 2021, estimates for 2022, and projections of compound annual growth rates (CAGRs) through 2027
  • Highlights of the current and future market potential for ML in life sciences application, and areas of focus to forecast this market into various segments and sub-segments
  • Estimation of the actual market size for machine learning in life sciences in USD million values, and corresponding market share analysis based on solutions offering, mode of deployment, application, and geographic region
  • Updated information on key market drivers and opportunities, industry shifts and regulations, and other demographic factors that will influence this market demand in the coming years (2022-2027)
  • Discussion of the viable technology drivers through a holistic review of various platform technologies for new and existing applications of machine learning in the life sciences areas
  • Identification of the major stakeholders and analysis of the competitive landscape based on recent developments and segmental revenues
  • Emphasis on the major growth strategies adopted by leading players of the global machine learning in life sciences market, their product launches, key acquisitions, and competitive benchmarking
  • Profile descriptions of the leading market players, including Alteryx Inc., Canon Medical Systems Corp., Hewlett Packard Enterprise (HPE), KNIME AG, Microsoft Corp., and Phillips Healthcare

Key Topics Covered:

Chapter 1 Introduction

Chapter 2 Summary and Highlights

Chapter 3 Market Overview
3.1 Introduction
3.1.1 Understanding Artificial Intelligence in Healthcare
3.1.2 Artificial Intelligence in Healthcare Evolution and Transition

Chapter 4 Impact of the Covid-19 Pandemic
4.1 Introduction
4.1.1 Impact of Covid-19 on the Market

Chapter 5 Market Dynamics
5.1 Market Drivers
5.1.1 Investment in Ai Health Sector
5.1.2 Rising Chronic Diseases
5.1.3 Advanced, Precise Results
5.1.4 Increasing Research and Development Budget
5.2 Market Restraints and Challenges
5.2.1 Reluctance Among Medical Practitioners to Adopt Ai-Based Technologies
5.2.2 Privacy and Security of User Data
5.2.3 Hackers and Machine Learning
5.2.4 Ambiguous Regulatory Guidelines for Medical Software
5.3 Market Opportunities
5.3.1 Untapped Potential in Emerging Markets
5.4 Value Chain Analysis

Chapter 6 Market Breakdown by Offering
6.1 Software
6.1.1 Market Size and Forecast
6.2 Services
6.2.1 Market Size and Forecast

Chapter 7 Market Breakdown by Deployment Mode
7.1 Cloud
7.1.1 Market Size and Forecast
7.2 On-Premises
7.2.1 Market Size and Forecast

Chapter 8 Market Breakdown by Application
8.1 Diagnosis
8.1.1 Market Size and Forecast
8.2 Therapy
8.2.1 Market Size and Forecast
8.3 Healthcare Management
8.3.1 Market Size and Forecast

Chapter 9 Market Breakdown by Region
9.1 Global Market
9.2 North America
9.2.1 U.S.
9.2.1 Canada
9.3 Europe
9.3.1 Germany
9.3.2 U.K.
9.3.3 France
9.3.4 Italy
9.3.5 Spain
9.3.6 Rest of Europe
9.4 Asia-Pacific
9.4.1 China
9.4.2 Japan
9.4.3 India
9.4.4 Rest of Asia-Pacific
9.5 Rest of the World

Chapter 10 Regulations and Finance
10.1 Regulatory Framework
10.1.1 American Diabetes Association’s Standards of Medical Care in Diabetes
10.1.2 Ata Guidelines for Artificial Intelligence
10.1.3 Indian Ai Guidelines, Strategy, and Standards

Chapter 11 Competitive Landscape
11.1 Overview
11.1.1 Development
11.1.2 Cloud
11.1.3 Users
11.1.4 Parent Market: Global Artificial Intelligence Market

Chapter 12 Company Profiles

  • Alteryx Inc.
  • Anaconda, Inc.
  • Canon Medical Systems Corp.
  • Enlitic Inc.
  • Hewlett Packard Enterprise (Hpe)
  • Imagen Technologies
  • Ibm Corp.
  • Intel Corp.
  • Knime AG
  • Microsoft Corp.
  • Nvidia
  • Oracle Corp.
  • Philips Healthcare
  • Sas Institute Inc.

For more information about this report visit https://www.researchandmarkets.com/r/9dmx00

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Artificial Intelligence

PractiTest Pushes Boundaries of Test Management with Milestones Release

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REHOVOT, Israel, May 6, 2024 /PRNewswire/ — PractiTest, a leader in innovative test management solutions, continues to push the boundaries with the release of Milestones, a powerful project management module enabling QA teams to align and stay connected to business goals. PractiTest’s New Milestones Module empowers QA teams to define high-level testing objectives within set timeframes. This results in well-defined roadmaps for sprint planning, major releases, or other pivotal project Milestones. By setting these objectives, QA teams gain a focused understanding of their contribution to broader business objectives and deadlines.

“Milestones have given us increased granularity in our ability to organize our testing,” says Tony, a system engineer at Battelle. “Having traceability was good, but Milestones allow us to plan much more clearly and easily.”
Milestones establish a seamless link between QA initiatives and overarching business strategies, ensuring testing efforts directly contribute to achieving company objectives. By defining clear testing objectives and schedules for each project phase, QA teams can stay on track and ensure efficient use of resources. The Milestones module also improves visibility, providing a high-level overview of the entire testing process and promoting seamless communication and collaboration among cross-functional teams.
PractiTest’s Commitment to Innovation
The release of Milestones reaffirms PractiTest’s dedication to providing cutting-edge solutions that empower QA teams to thrive.
“In today’s competitive environment, ensuring QA aligns with business objectives is imperative,” says Yaniv Iny, CEO of PractiTest. “The Milestones module is a testament to our commitment to empowering QA teams to evolve into strategic partners, fostering quality and delivering tangible outcomes while staying in sync with overarching business objectives.”
About PractiTest
PractiTest is an end-to-end test management platform designed to simplify and untangle complexity for complex and robust environments. PractiTest centralizes all your QA work, processes, teams, and tools into one platform to bridge silos, unify communication, and enable one source of truth across your organization. With PractiTest you can make informed data-driven decisions based on end-to-end visibility provided by customizable reports, real-time dashboards, and dynamic filter views.
For more information about PractiTest visit: https://www.practitest.com/
Media Contact:May [email protected]
Logo: https://mma.prnewswire.com/media/1997506/PractiTest_Logo.jpg

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Artificial Intelligence

EZVIZ unveils its groundbreaking H9c Dual-lens Smart Pan-and-tilt Camera series: a new paradigm for automated, all-round outdoor protection

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By combining a pan-and-tilt panoramic lens and a fixed 180-degree wide-angle lens, one H9c Dual smartly secures large areas with performance better than that of two ordinary ones.
HOOFDDORP, Netherlands, May 6, 2024 /PRNewswire/ — EZVIZ, a leading global player in innovative smart home security, proudly introduces the H9c Dual series, its latest dual-lens outdoor pan-and-tilt cameras that redefine smart protection for homes and small businesses. With options in 2K and 3K resolutions, their groundbreaking design combines a sharp bullet camera and a flexible PT camera, addressing complex security needs effectively. The interlinked dual lenses work collaboratively to safeguard wide property areas, detect and track activities, and offer auto-patrol options for hands-free security.

“The H9c Dual challenges traditional outdoor cameras with unrivaled vision, unmatched automation, and high versatility for basically any scenario,” said Candice Tu, the lead product manager, “EZVIZ leads the way in the development and application of advanced dual-lens technology. This underlines our dedication to bringing cutting-edge technology within reach for practical, everyday situations.”
At the core of the H9c Dual is its groundbreaking dual-lens technology, highlighted by EZVIZ’s distinctive co-action function. The two lenses can work independently at two static viewing angles or act together as a team. When the fixed lens detects motions, the pan-and-tilt lens automatically rotates to track the same activity. This co-action function can also be manually controlled through the EZVIZ App.
The series addresses unnoticed blind spots by offering a 180-degree comprehensive view in a single frame, supplemented by the bottom PT lens for intricate close-ups. Both lenses, with high resolutions of 2K/3K, use built-in AI chips to detect people and vehicles in customizable zones, ensuring users are informed of crucial activities. Users can set up to four patrol spots for the PT lens to complete automatic rotations on a schedule.
Equipped with powerful LEDs, the H9c Dual provides color night vision up to 40 meters and warns potential trespassers with a loud siren and dazzling flashlight upon detection. Offering superior protection compared to a traditional two-camera system, the H9c is a breeze to set up thanks to its adaptable mounting design. Users can manage and control their H9c through the user-friendly EZVIZ App, and enjoy seamless integration with prevailing voice assistants and the larger EZVIZ ecosystem.
Learn more at www.ezviz.com.
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Artificial Intelligence

Red light therapy for repairing spinal cord injury passes milestone

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BIRMINGHAM, England, May 6, 2024 /PRNewswire/ — Patients with spinal cord injury (SCI) could benefit from future treatment to repair nerve connections using red and near-infrared light.

The method, invented by University of Birmingham scientists and patented by University of Birmingham Enterprise, delivers light directly to the site of the injury. 
Their latest research, published in Bioengineering and Translational Medicine, determined an optimal ‘dose’ for this novel approach, and showed it can deliver therapeutic improvements including significant restoration of sensation and movement, and regeneration of damaged nerve cells. 
Researchers led by Professor Zubair Ahmed used cell models of SCI to determine the frequency and duration of light required to achieve maximum restoration of function and stimulate nerve cell regrowth. 
They found delivery at a wavelength of 660nm for one minute a day increased cell viability (the number of live cells) by 45% over five days’ treatment. 
Professor Ahmed said: “The effect of 660nm light was both neuroprotective, meaning it improved survival of nerve cells, and neuroregenerative, meaning it stimulated nerve cell growth.” 
The researchers also investigated the effect of light therapy in preclinical models of SCI, using an implantable device and transcutaneous delivery with the light source placed against the skin. They showed comparable results for both methods, with a one-minute dose of 660nm light, delivered daily for seven days resulting in reduced tissue scarring, increased levels of proteins associated with nerve cell regeneration, improvements in the connections between cells and significant functional recovery. 
This is the first time transcutaneous and direct light delivery have been compared in SCI. Professor Ahmed said: “To make light therapy viable for treating SCI in humans an implantable device will be required, to provide line of sight to damaged tissue and the opportunity for greater accuracy and standardise dosing without impedance due to the thickness of the skin and other tissues surrounding the spinal cord.”
The researchers are planning to develop an implantable device for use in humans with traumatic SCI. They have already received further funding and are seeking commercial partners or investors to develop a prototype device to take into first-in-man clinical trials.
Full release here. 
University of Birmingham Enterprise helps researchers turn ideas into products and services that meet real-world needs. Follow us on LinkedIn and X.
Photo: https://mma.prnewswire.com/media/2404909/University_of_Birmingham_Enterprise.jpg
Media enquiries: Ruth Ashton
Commercial enquiries: Veemal Bhowruth

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