Dermatology

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preterm infants due to the potential for the adhesive electrodes of conventional electrocardiogram (ECG) to cause damage to the epidermis. This study was performed to evaluate the agreement between HR and RR measurements of preterm infants using a non-contact computer vision system with comparison to meas...

Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction.

Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed malignant or benign - depending upon the severity of the infection and the current stage. The conventional methods require a detailed physical inspection by an expert dermatologist, which is time-consuming and imprecise. Therefore, several computer vision methods are introduced lately, which are cost-effe...

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-hea...

Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.

BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reve...

Automated identification of malignancy in whole-slide pathological images: identification of eyelid malignant melanoma in gigapixel pathological slides using deep learning.

BACKGROUND/AIMS: To develop a deep learning system (DLS) that can automatically detect malignant melanoma (MM) in the eyelid from histopathological se...

The Application of Deep Learning in the Risk Grading of Skin Tumors for Patients Using Clinical Images.

According to diagnostic criteria, skin tumors can be divided into three categories: benign, low degree and high degree malignancy. For high degree mal...

Natural language processing of Reddit data to evaluate dermatology patient experiences and therapeutics.

BACKGROUND: There is a lack of research studying patient-generated data on Reddit, one of the world's most popular forums with active users interested...

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain.

Melanoma Detection by Means of Multiple Instance Learning.

We present an application to melanoma detection of a multiple instance learning (MIL) approach, whose objective, in the binary case, is to discriminat...

Using machine learning-based lesion behavior mapping to identify anatomical networks of cognitive dysfunction: Spatial neglect and attention.

Previous lesion behavior studies primarily used univariate lesion behavior mapping techniques to map the anatomical basis of spatial neglect after rig...

ASO Author Reflections: Robotic Pelvic Lymph Node Dissection for Metastatic Melanoma-A Minimally Invasive Approach to a Difficult Problem.

Machine learning in breast MRI.

Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to br...

Detection of Skin Cancer Using SVM, Random Forest and kNN Classifiers.

Most common and deadly type of cancer is Skin cancer. The destructive kind of cancers in skin is Melanoma as well as it can be identified at the initi...

In-Bore Transrectal MRI-Guided Biopsy With Robotic Assistance in the Diagnosis of Prostate Cancer: An Analysis of 57 Patients.

The objective of our study was to analyze the feasibility and potential role of robotic-assisted transrectal MRI-guided biopsy for the diagnosis of p...

Improved Deep Learning Network Based in combination with Cost-sensitive Learning for Early Detection of Ovarian Cancer in Color Ultrasound Detecting System.

With the development of theories and technologies in medical imaging, most of the tumors can be detected in the early stage. However, the nature of ov...

A case of robotic assisted percutaneous coronary intervention of the left main coronary artery in a patient with very late baffle stenosis after surgical correction of anomalous left coronary artery from the pulmonary artery.

A 34-year-old woman with history of surgical correction (Takeuchi procedure) of anomalous left coronary artery from the pulmonary artery (ALCAPA) pres...

Assessing the effectiveness of artificial intelligence methods for melanoma: A retrospective review.

BACKGROUND: Artificial intelligence methods for the classification of melanoma have been studied extensively. However, few studies compare these metho...

Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions.

BACKGROUND: In recent months, multiple publications have demonstrated the use of convolutional neural networks (CNN) to classify images of skin cancer...

Self-Paced Balance Learning for Clinical Skin Disease Recognition.

Class imbalance is a challenging problem in many classification tasks. It induces biased classification results for minority classes that contain less...

[Artificial Intelligence in Endoscopy: Deep Neural Nets for Endoscopic Computer Vision - Methods & Perspectives].

Artificial neural networks, as a specific approach towards artificial intelligence (AI), can open up a variety of new perspectives for endoscopy, such...