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Deep Vision: Near-infrared imaging and machine learning can identify hidden tumors


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IMAGE: The machine learning technique developed by Dr. Takemura and team could distinguish tumor tissue from healthy tissue in ex vivo images of resected tumors, with 86% accuracy.
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Credit: Hiroshi Takemura from Tokyo University of Science
Tumors can be damaging to surrounding blood vessels and tissues even if they re benign. If they re malignant, they re aggressive and sneaky, and often irrevocably damaging. In the latter case, early detection is key to treatment and recovery. But such detection can sometimes require advanced imaging technology, beyond what is available commercially today.
For instance, some tumors occur deep inside organs and tissues, covered by a mucosal layer, which makes it difficult for scientists to directly observe them with standard methods like endoscopy (which inserts a small camera into a patient s body via a thin tube) or reach them during biopsies. In particular, gastrointestinal stromal tumors (GISTs) ....

Hiroaki Ikematsu , Hideo Yokotad Eng , Tomonori Yano , Daiki Sato , Kohei Soga , Masao Kamimura , Hideo Yokota , Yuichi Kitagawa , Hiroshi Takemura , Naoki Hosokawa , Takeshi Kuwata , Tomohiro Kadota , Masakazu Umezawa , Takahiro Kinoshita , Toshihiro Takamatsu , Kosuke Maeda , Kazuhiro Kaneko , Kyohei Okubo , Tetsuo Akimoto , Course Of Advanced Clinical Research Cancer , Division Of Radiation Oncology , Department Of Gastric Surgery , Juntendo University Graduate School Of Medicine , Research Institute For Biomedical Sciences , Department Of Mechanical Engineering , National Cancer Center Hospital ,

Early Outcomes of a National Cancer Center's Strategy Against COVID-19 Executed Through a Disease Outbreak Response Taskforce.


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Early Outcomes of a National Cancer Center s Strategy Against COVID-19 Executed Through a Disease Outbreak Response Taskforce.
January 15, 2021
We present the strategy of a comprehensive cancer center organized to make operations pandemic proof and achieve continuity of cancer care during the COVID-19 pandemic.
Disease Outbreak Response (DORS) measures implemented at our center and its satellite clinics included strict infection prevention, manpower preservation, prudent resource allocation, and adaptation of standard-of-care treatments. Critical day-to-day clinical operations, number of persons screened before entry, staff temperature monitoring, and personal protection equipment stockpile were reviewed as a dashboard at daily DORS taskforce huddles. Polymerase chain reaction swab tests performed for patients and staff who met defined criteria for testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were tracked. Descriptive st ....

Ravindran Kanesvaran , Swee Peng Yap , Patricia Sh Neo , Jackj Chan , Jin Wei Kwek , Michael Lc Wang , William Yk Hwang , Claramaes Chia , Division Of Radiation Oncology , Department Of Pharmacy , Division Of Oncologic Imaging , Oncology Academic Clinical Program , National Cancer Centre Singapore , Outbreak Response , Wei Kwek , Chee Kian Tham , Litast Chew , Hiang Khoon Tan , Soon Thye , Oncologic Imaging , Radiation Oncology , ஸ்வீ பெங் யாப் , பாட்ரிசியா ஷ நியோ , மைக்கேல் எல்சி வாங் , வில்லியம் யக் ஹ்வ்யாஂக் , பிரிவு ஆஃப் கதிர்வீச்சு புற்றுநோயியல் ,