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Markey Study Shows Kentucky Endometrial Cancer Patients Have Higher Rates of DACH1 Mutation

A new study by Markey researchers shows a higher-than-average rate of DACH1 mutations in Kentucky patients with endometrial cancer.
LEXINGTON, Ky. (Jan. 12, 2020) A new study by University of Kentucky Markey Cancer Center researchers shows that DACH1 mutations are prevalent in Kentucky patients with endometrial cancer, suggesting that DACH1 may be a candidate biomarker for future trials with immunotherapy.
DACH1 is a transcriptional repressor and tumor suppressor gene that is frequently mutated in other cancers, including melanoma, bladder and prostate cancer. The loss of DACH1 expression is also associated with poor prognosis and reduced survival in women with uterine cancer.
Published in PLOS One, the study sought to determine the frequency of DACH1 mutations in patients with endometrial cancer in Kentucky. Using the Oncology Research Information Exchange Network (ORIEN), a personalized medicine consortium that Markey joined in 2017, researchers examined clinical ....

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IT News Online - Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More

Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More
JCN Newswire
2020-12-17
KAWASAKI, Japan, Dec 17, 2020 - (JCN Newswire) - Fujitsu Laboratories, Ltd. has successfully developed a technology that uses AI to discover the characteristic cause-and-effect relationships in various pieces of data relating to people and things in a variety of fields, with possible applications in medicine, marketing, manufacturing, and more.
Image of the developed technology
The technology specifically addresses the need to isolate and identify characteristics from data in different real-world scenarios. In the medical field, for example, it is necessary to identify the characteristic genes that affect the development of cancer in individual patients. In the field of marketing, sales representatives need to find the characteristic factors that lead individual customers to make a purchase. Fujitsu ha ....

United States , Nakagami Gun , Nishihara Cho , Daisuke Utsumi , Mutsumi Nishida , Kenzo Takahashi , Takuya Miyagi , School Of Medicine , University Of The Ryukyus Location , Us Broad Institute , National Cancer Institute , Wide Learning Technology , Fujitsu Laboratories Ltd , Fujitsu Limited , National Human Genome Research Institute , Department Of Dermatology , University Of The Ryukyus , Fujitsu Develops Technology , Discover Characteristic Causal Relationships , Individual Data , Professor Kenzo Takahashi , Assistant Professor Takuya Miyagi , Assistant Professor Daisuke Utsumi , Graduate School , Fujitsu Laboratories , Cancer Genome Atlas ,

Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More – IT Business Net

Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More
KAWASAKI, Japan, Dec 17, 2020 – (JCN Newswire) – Fujitsu Laboratories, Ltd. has successfully developed a technology that uses AI to discover the characteristic cause-and-effect relationships in various pieces of data relating to people and things in a variety of fields, with possible applications in medicine, marketing, manufacturing, and more.
Image of the developed technology
The technology specifically addresses the need to isolate and identify characteristics from data in different real-world scenarios. In the medical field, for example, it is necessary to identify the characteristic genes that affect the development of cancer in individual patients. In the field of marketing, sales representatives need to find the characteristic factors that lead individual customers to make a purchase. Fujitsu has developed a technology to discover ....

United States , Nakagami Gun , Nishihara Cho , Daisuke Utsumi , Mutsumi Nishida , Kenzo Takahashi , Takuya Miyagi , School Of Medicine , University Of The Ryukyus Location , Us Broad Institute , National Cancer Institute , Wide Learning Technology , Fujitsu Laboratories Ltd , Fujitsu Limited , National Human Genome Research Institute , Department Of Dermatology , University Of The Ryukyus , Fujitsu Laboratories , Professor Kenzo Takahashi , Assistant Professor Takuya Miyagi , Assistant Professor Daisuke Utsumi , Graduate School , Cancer Genome Atlas , Highly Precise Learning Even , Imbalanced Data Sets , Ryukyus Location ,

Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More

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KAWASAKI, Japan, Dec 17, 2020 - (JCN Newswire) - Fujitsu Laboratories, Ltd. has successfully developed a technology that uses AI to discover the characteristic cause-and-effect relationships in various pieces of data relating to people and things in a variety of fields, with possible applications in medicine, marketing, manufacturing, and more.
Image of the developed technology
The technology specifically addresses the need to isolate and identify characteristics from data in different real-world scenarios. In the medical field, for example, it is necessary to identify the characteristic genes that affect the development of cancer in individual patients. In the field of marketing, sales representatives need to find the characteristic factors that lead individual customers to make a purchase. Fujitsu has developed a technology to discover the characteristic causality of individual pieces of data by quickly extracting all the groups of data that have a common correl ....

United States , Nakagami Gun , Nishihara Cho , Daisuke Utsumi , Mutsumi Nishida , Kenzo Takahashi , Takuya Miyagi , Fujitsu Ltd , School Of Medicine , University Of The Ryukyus Location , Us Broad Institute , National Cancer Institute , Wide Learning Technology , Fujitsu Laboratories Ltd , Fujitsu Limited , National Human Genome Research Institute , Department Of Dermatology , University Of The Ryukyus , Professor Kenzo Takahashi , Assistant Professor Takuya Miyagi , Assistant Professor Daisuke Utsumi , Graduate School , Fujitsu Laboratories , Cancer Genome Atlas , Highly Precise Learning Even , Imbalanced Data Sets ,