BCG GAMMA, in Collaboration with Scikit-Learn, Launches FACET, Its New Open-Source Library …

BCG GAMMA, in Collaboration with Scikit-Learn, Launches FACET, Its New Open-Source Library …

BOSTON, Jan. 12, 2021 /PRNewswire/ — Boston Consulting Group (BCG) has released its first open-source software library for human-explainable artificial intelligence (AI). BCG GAMMA FACET enables users to make better business decisions by opening the “black box” of advanced machine learning models. Advances in AI have given data scientists powerful tools to analyze complex business problems and predict outcomes. FACET goes one step further, giving data scientists and business experts a new way to understand how a model arrives at predictions. With this new insight, data scientists can use machine learning models to inform decisions that save money, maximize yield, retain customers, remove bias, and improve patient outcomes.

BCG believes that humans must always be at the core of all AI-based decisions. By helping developers and business users understand how algorithms analyze the data sets on which AI predictions are based, BCG GAMMA FACET reestablishes human control over and trust in AI. It uses a newly developed model-inspection algorithm to explain the relationships between the model variables. And it applies a simulation approach to enable data scientists to conduct “virtual experiments” to determine how changes in these variables can affect predicted outcomes.

“Data scientists are often under pressure to explain the behavior of their models. This is precisely the aim of FACET: to explain the key variables in the models very quickly, in order to provide greater clarity in the dialogue between data scientists and operational teams. By facilitating the explicability of models, FACET contributes to the deployment of a more transparent and more responsible AI,” says Sylvain Duranton, BCG managing director, senior partner, and global leader of BCG GAMMA.

“We are very glad that scikit-learn’s simple and consistent design allowed BCG to develop FACET, a very valuable tool for our community,” says Alexandre Gramfort, senior research scientist at Inria, co-author, and member of the scikit-learn technical committee.

“BCG GAMMA is very excited to join the open-source data science community with our public release of FACET,” says Jan Ittner, BCG partner, associate director, and leader of the BCG GAMMA FACET team. “We look forward to working with the data science community and in partnership with scikit-learn to make AI more useful and understandable for everyone.”

BCG GAMMA FACET is an intuitive, easy-to-implement, open-source software library available to the global data science community.

For more information about BCG GAMMA FACET, please contact Sophie Ruedinger at +49 170 334 4530 or [email protected].

For more media queries, please contact Eric Gregoire at +1 617 850 3783 or [email protected].

BCG GAMMA is BCG’s global team dedicated to applying artificial intelligence and advanced analytics to critical business problems at leading companies and organizations. The team includes 900-plus data scientists and engineers who utilize AI and advanced analytics (e.g., machine learning, deep learning, optimization, simulation, natural language and image analytics, etc.) to build solutions that transform business performance. BCG GAMMA’s approach builds value and competitive advantage at the intersection of data science, technology, people, business processes, and ways of working. For more information, please visit our webpage.

About Boston Consulting Group
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation—inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.

To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.

SOURCE Boston Consulting Group (BCG)

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Published at Tue, 12 Jan 2021 04:52:30 +0000

Artificial Intelligence In Healthcare Diagnosis Market Business Opportunity to 2027 – Top …

Artificial intelligence (AI) uses algorithms and software to perform certain tasks without human intervention and instructions. AI represents the integration of technologies such as machine learning, natural language processing, reasoning, and perception. It is used in healthcare for approximation of human cognition as well as the analysis of complex medical and diagnostic imaging data. The artificial intelligence in healthcare diagnosis market is driven by the ability of AI to provide improved outcomes; moreover, the growing need to increase coordination between healthcare workforce and patients also supports the market growth. The rise in the importance of Big Data in healthcare, increase in the adoption of precision medicine, and surge in venture capital investments also contribute to the market growth.

The artificial intelligence in healthcare diagnosis market was valued at US$ 3,639.02 million in 2019 and is projected to reach US$ 66,811.97 million by 2027; it is expected to grow at a CAGR of 44.0% during 2020–2027.

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Competitive Landscape: General Electric Company; Aidoc; Arterys Inc.; icometrix; IDx Technologies Inc; MaxQ AI Ltd.; Caption Health, Inc; Zebra Medical Vision, Inc.; Siemens Healthineers AG; and Koninklijke Philips 

Factors such as the rising adoption of artificial intelligence in disease identification and diagnosis and increasing investments in AI healthcare startups are driving the growth of the AI in healthcare diagnosis market. However, the lack of skilled workforce and ambiguity of regulatory guidelines for medical software impede the market growth. Further, the increasing potential in emerging economies offers significant opportunities for the future growth of the global artificial intelligence in healthcare diagnosis market players.

Tokyo-based AI Medical Service, the Japanese startup developing the AI-powered technology to detect cancerous lesions from endoscopic footage, announced in October 2019 that it had secured about USD $43 million US (about 4.6 billion yen) in a Series B round. Healthcare analytics firm Tricog has raised USD $10.5 million in a Series B round of funding. Using Artificial Intelligence and Machine Learning, the startup helps in the wellness, screening, and diagnosis of acute as well as chronic heart diseases. The investment comes in from UTEC – The University of Tokyo Edge Capital, Japan; Aflac Ventures, LLC, Japan; TeamFund, USA; and Dream Incubator, Japan, and also saw participation from Inventus Capital and Blume Ventures. Using Artificial Intelligence and Machine Learning, the five-year-old startup has helped 3 million patients globally. It also uses its virtual cardiology services to help in remote clinics.

Artificial Intelligence in healthcare is one of the most significant technological advances in medicine thus far. Startups developing AI-driven imaging & diagnostic solutions are the major factors responsible for the growth of the market in the study period. China, the US, and the UK are emerging as a popular hub for healthcare innovations. China-based healthcare AI startups have benefited from the government’s AI-focused development strategy, inspiring investment, and private-public partnerships. Additionally, the British government has announced a National Artificial Intelligence Lab that will collaborate with Britain’s universities and technology companies to research on cancer, dementia, and heart disease. UK-based startups have benefited from the government’s robust library of patient data, as British citizen’s share their anonymous healthcare data with the British National Health Service.

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Published at Tue, 12 Jan 2021 03:56:15 +0000

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