NEW YORK (360Dx) – Google researchers have found that a deep-learning approach could help pathologists better detect cancer in patients, they recently reported on the company's research blog.

Applying deep-learning methods, they created an automated detection algorithm that could detect 89 percent of tumors from microscopy images compared to 73 percent for pathologists, who hypothetically would have an unlimited amount of time to examine pathology slides.

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Oct
02

In the last few years several molecular testing methodologies — such as immunohistochemistry, PCR, and sequencing — have been approved by the US Food and Drug Administration to aid in the management of patients with lung cancer.  

Oct
04

This webinar will discuss the use of new software tools to support the diagnosis of CTFR-related disorders using next-generation sequencing.

Oct
10

This webinar will provide a first-hand look at how the Dana-Farber Cancer Center is adapting its oncology care strategy in light of the rapidly evolving molecular landscape.

Nov
05
Sponsored by
Sophia Genetics

With the Next Generation Sequencing (NGS), genomes sequencing has been democratized over the last decades with the detection of genomic alterations, thus replacing Sanger sequencing.