AIMC Topic: Humans

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Handling imbalanced medical image data: A deep-learning-based one-class classification approach.

Artificial intelligence in medicine
In clinical settings, a lot of medical image datasets suffer from the imbalance problem which hampers the detection of outliers (rare health care events), as most classification methods assume an equal occurrence of classes. In this way, identifying ...

TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine.

Computational and mathematical methods in medicine
Extracting the tongue body accurately from a digital tongue image is a challenge for automated tongue diagnoses, as the blurred edge of the tongue body, interference of pathological details, and the huge difference in the size and shape of the tongue...

Design of Festival Sentiment Classifier Based on Social Network.

Computational intelligence and neuroscience
With the development of society, more and more attention has been paid to cultural festivals. In addition to the government's emphasis, the increasing consumption in festivals also proves that cultural festivals are playing increasingly important rol...

Accuracy of Trained Physicians is Inferior to Deep Learning-Based Algorithm for Determining Angles in Ultrasound of the Newborn Hip.

Ultraschall in der Medizin (Stuttgart, Germany : 1980)
PURPOSE:  Sonographic diagnosis of developmental dysplasia of the hip allows treatment with a flexion-abduction orthosis preventing hip luxation. Accurate determination of alpha and beta angles according to Graf is crucial for correct diagnosis. It i...

Deep Learning-based Quantification of Abdominal Subcutaneous and Visceral Fat Volume on CT Images.

Academic radiology
RATIONALE AND OBJECTIVES: Develop a deep learning-based algorithm using the U-Net architecture to measure abdominal fat on computed tomography (CT) images.

Current and future applications of artificial intelligence in pathology: a clinical perspective.

Journal of clinical pathology
During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming yea...

Machine learning for predicting long-term kidney allograft survival: a scoping review.

Irish journal of medical science
Supervised machine learning (ML) is a class of algorithms that "learn" from existing input-output pairs, which is gaining popularity in pattern recognition for classification and prediction problems. In this scoping review, we examined the use of sup...

Robotic Partial Segment VIII Resection.

Annals of surgical oncology
BACKGROUND:: Robotic partial hepatectomy is an important tool for the treatment of colorectal liver metastases, offering the benefits of a minimally invasive approach with advanced wristed motion, precision, and dexterity. We demonstrate the steps of...

[Robot-assisted Mediastinal Mass Resection].

Zentralblatt fur Chirurgie
In recent years, robot-assisted thoracic surgery is gaining more and widespread interest in Europe. Due to the narrow space and the complexity of anatomical structures, conventional minimally invasive mediastinal surgery may be challenging for the th...

Artificial Intelligence Solutions for Analysis of X-ray Images.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conve...