Physical and engineering sciences in medicine
Mar 1, 2023
The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate patient management and outcome improvement. However, the disease progression is influenced by multi...
Post-induction hypotension is common and associated with postoperative complications. We hypothesised that pneumatic leg compression reduces post-induction hypotension in elderly patients undergoing robot-assisted laparoscopic prostatectomy. In this ...
Identifying hit compounds is an important step in drug development. Unfortunately, this process continues to be a challenging task. Several machine learning models have been generated to aid in simplifying and improving the prediction of candidate co...
OBJECTIVES: Patients with T4 obstructive colorectal cancer (OCC) have a high mortality rate. Therefore, an accurate distinction between T4 and T1-T3 (NT4) in OCC is an important part of preoperative evaluation, especially in the emergency setting. Th...
: The classification of breast cancer is performed based on its histological subtypes using the degree of differentiation. However, there have been low levels of intra- and inter-observer agreement in the process. The use of convolutional neural netw...
The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genet...
Asian Pacific journal of cancer prevention : APJCP
Mar 1, 2023
OBJECTIVE: This study aims to develop automatic breast tumor detection and classification including automatic tumor volume estimation using deep learning techniques based on computerized analysis of breast ultrasound images. When the skill levels of ...
IMPORTANCE: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups.
IMPORTANCE: Artificial intelligence (AI) enables powerful models for establishment of clinical diagnostic and prognostic tools for hip fractures; however the performance and potential impact of these newly developed algorithms are currently unknown.
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