1x
Velocità di riproduzione- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- 1
- 1.1
- 1.2
- 1.3
- 1.5
- 2
ai: scientists discover high-risk form of endometrial cancer and how to test for it. a discovery by researchers at the university of british columbia promises to improve care for patients with endometrial cancer, the most common gynecologic malignancy. a discovery by researchers at the university of british columbia promises to improve care for patients with endometrial cancer, the most common gynecologic malignancy. using artificial intelligence (ai) to spot patterns across thousands of cancer cell images, the researchers have pinpointed a distinct subset of endometrial cancer that puts patients at much greater risk of recurrence and death, but would otherwise go unrecognized by traditional pathology and molecular diagnostics. the findings, published today in nature communications, will help doctors identify patients with high-risk disease who could benefit from more comprehensive treatment. “endometrial cancer is a diverse disease, with some patients much more likely to see their cancer return than others,” said dr. jessica mcalpine, professor and dr. chew wei chair in gynaecologic oncology at ubc, and surgeon-scientist at bc cancer and vancouver general hospital. “it’s so important that patients with high-risk disease are identified so we can intervene and hopefully prevent recurrence. this ai-based approach will help ensure no patient misses an opportunity for potentially lifesaving interventions.”. ai-powered precision medicine. the discovery builds on work by dr. mcalpine and colleagues at b.c.’s gynecologic cancer initiative — a multi-institutional collaboration between ubc, bc cancer, vancouver coastal health and bc women’s hospital — who in 2013 helped show that endometrial cancer can be classified into four subtypes based on the molecular characteristics of cancerous cells, with each posing a different level of risk to patients. continua a leggere su salutedomani.com.
Using artificial intelligence (AI) to spot patterns across thousands of cancer cell images, the researchers have pinpointed a distinct subset of endometrial cancer that puts patients at much greater risk of recurrence and death, but would otherwise go unrecognized by traditional pathology and molecular diagnostics.
The findings, published today in Nature Communications, will help doctors identify patients with high-risk disease who could benefit from more comprehensive treatment. “Endometrial cancer is a diverse disease, with some patients much more likely to see their cancer return than others,” said Dr. Jessica McAlpine, professor and Dr. Chew Wei Chair in Gynaecologic Oncology at UBC, and surgeon-scientist at BC Cancer and Vancouver General Hospital. “It’s so important that patients with high-risk disease are identified so we can intervene and hopefully prevent recurrence. This AI-based approach will help ensure no patient misses an opportunity for potentially lifesaving interventions.”
AI-powered precision medicine
The discovery builds on work by Dr. McAlpine and colleagues at B.C.’s Gynecologic Cancer Initiative — a multi-institutional collaboration between UBC, BC Cancer, Vancouver Coastal Health and BC Women’s Hospital — who in 2013 helped show that endometrial cancer can be classified into four subtypes based on the molecular characteristics of cancerous cells, with each posing a different level of risk to patients.
CONTINUA A LEGGERE SU SALUTEDOMANI.COM
