PURPOSE: To develop and compare deep learning (DL) algorithms to detect keratoconus on the basis of corneal topography and validate with visualization methods.
BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (∼10%) of metastasis to lymph nodes. To reduce unnecessary surgical rese...
Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more challenging to differentiate coronavirus disease 2019 (COVID-19) pneumonia from non-COVID-19 pneumonia o...
International journal of urology : official journal of the Japanese Urological Association
Sep 24, 2020
OBJECTIVES: To analyze the correlation between periprostatic fat thickness on multiparametric magnetic resonance imaging and upstaging from cT1/2 to pT3 in robot-assisted radical prostatectomy.
The international journal of medical robotics + computer assisted surgery : MRCAS
Sep 24, 2020
BACKGROUND: This study aimed to compare short- and long-term outcomes after robotic versus laparoscopic approach in patients undergoing curative surgery for rectal cancer.
BACKGROUND: Completion axillary lymph node dissection is overtreatment for patients with sentinel lymph node (SLN) metastasis in whom the metastatic risk of residual non-SLN (NSLN) is low. However, the National Comprehensive Cancer Network panel posi...
For treatment individualisation of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with primary radiochemotherapy, we explored the capabilities of different deep learning approaches for predicting loco-regional tu...
Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on ches...
BACKGROUND: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics.
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