AIMC Topic: Humans

Clear Filters Showing 40001 to 40010 of 95995 articles

Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic prediction.

Abdominal radiology (New York)
PURPOSE: The purpose of this study is to compare fully automated CT-based measures of adipose tissue at the L1 level versus the standard L3 level for predicting mortality, which would allow for use at both chest (L1) and abdominal (L3) CT.

Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: To (1) develop a deep-learning (DL) algorithm capable of producing limb-length and knee-alignment measurements, and (2) determine the association between limb-length discrepancy (LLD), coronal-plane alignment, osteoarthritis (OA) severity, a...

Neurology education in the era of artificial intelligence.

Current opinion in neurology
PURPOSE OF REVIEW: The practice of neurology is undergoing a paradigm shift because of advances in the field of data science, artificial intelligence, and machine learning. To ensure a smooth transition, physicians must have the knowledge and compete...

Diseased thyroid tissue classification in OCT images using deep learning: Towards surgical decision support.

Journal of biophotonics
Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real-time automatic analysis could support t...

Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study.

Clinical chemistry and laboratory medicine
OBJECTIVES: To compare the artificial intelligence algorithms as powerful machine learning methods for evaluating patients with suspected sepsis using data from routinely available blood tests performed on arrival at the hospital. Results were compar...

Bayesian Disturbance Injection: Robust imitation learning of flexible policies for robot manipulation.

Neural networks : the official journal of the International Neural Network Society
Humans demonstrate a variety of interesting behavioral characteristics when performing tasks, such as selecting between seemingly equivalent optimal actions, performing recovery actions when deviating from the optimal trajectory, or moderating action...

Deep learning-based predictions of clear and eosinophilic phenotypes in clear cell renal cell carcinoma.

Human pathology
We have recently shown that histological phenotypes focusing on clear and eosinophilic cytoplasm in clear cell renal cell carcinoma (ccRCC) correlated with prognosis and the response to angiogenesis inhibition and checkpoint blockade. This study aims...

Bone tumor necrosis rate detection in few-shot X-rays based on deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Although biopsy-based necrosis rate is a golden standard for reflecting the sensitivity of bone tumor and guiding postoperative chemotherapy, it requires biopsy which is invasive and time-consuming. In this paper, we develop a new necrosis rate detec...

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization.

European journal of radiology
PURPOSE: Extracting water equivalent diameter (DW), as a good descriptor of patient size, from the CT localizer before the spiral scan not only minimizes truncation errors due to the limited scan field-of-view but also enables prior size-specific dos...