Dermatology

Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach.

Alopecia areata is defined as an autoimmune disorder that results in hair loss. The latest worldwide statistics have exhibited that alopecia areata has a prevalence of 1 in 1000 and has an incidence of 2%. Machine learning techniques have demonstrated potential in different areas of dermatology and may play a significant role in classifying alopecia areata for better prediction and diagnosis. We p...

Robotic enucleation of a biliary adenofibroma.

A 69-year-old man was referred to the hepatobiliary surgeons for mild enlargement of an asymptomatic cystic liver lesion found on routine screening in 2017 that measured 3.7×3.6×4.3 cm. Work-up with MRI revealed a complex multilocular cyst that had enlarged to 6.6×5.5×4.6 cm. Other work-up was unremarkable. He had a Eastern Cooperative Oncology Group score of 1; therefore, a surgical excision was ...

Artificial intelligence-assisted fast screening cervical high grade squamous intraepithelial lesion and squamous cell carcinoma diagnosis and treatment planning.

Every year cervical cancer affects more than 300,000 people, and on average one woman is diagnosed with cervical cancer every minute. Early diagnosis ...

Deep learning-based image reconstruction for TOF PET with DIRECT data partitioning format.

Conventional positron emission tomography (PET) image reconstruction is achieved by the statistical iterative method. Deep learning provides another o...

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease pro...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, studies its ability to distinguish benign and maligna...

Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.

PURPOSE: We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdomi...

Deep Learning-Based Computed Tomography Image Features in the Detection and Diagnosis of Perianal Abscess Tissue.

The performance characteristics of deep learning fully convolutional neural network (DLFCNN) algorithm-based computed tomography (CT) images were inve...

Artificial Intelligence in Dermatology: A Threat or an Opportunity?

The worldwide explosion of interest in artificial intelligence (AI) has created a before-and-after moment in our lives by generating great improvement...

Deep learning detects cardiotoxicity in a high-content screen with induced pluripotent stem cell-derived cardiomyocytes.

Drug-induced cardiotoxicity and hepatotoxicity are major causes of drug attrition. To decrease late-stage drug attrition, pharmaceutical and biotechno...

Cutaneous Ionogel Mechanoreceptors for Soft Machines, Physiological Sensing, and Amputee Prostheses.

Touch sensing has a central role in robotic grasping and emerging human-machine interfaces for robot-assisted prosthetics. Although advancements in so...

Simulation and machine learning modelling based comparative study of InAlGaN and AlGaN high electron mobility transistors for the detection of HER-2.

The detection of the cancer biomarker human epidermal growth factor receptor 2 (HER-2) has always been challenging at the early stages of cancer due t...

neoDL: a novel neoantigen intrinsic feature-based deep learning model identifies IDH wild-type glioblastomas with the longest survival.

BACKGROUND: Neoantigen based personalized immune therapies achieve promising results in melanoma and lung cancer, but few neoantigen based models perf...

Comparative Outcomes of Double-J and Cutaneous Pyeloureteral Stents in Pediatric Robot-Assisted Laparoscopic Pyeloplasty.

Comparative outcome studies investigating internal Double-J (DJ) and externalized stents have primarily been performed for open and laparoscopic pyel...

Computed Tomography Angiography under Deep Learning in the Treatment of Atherosclerosis with Rapamycin.

The clinical characteristics and vascular computed tomography (CT) imaging characteristics of patients were explored so as to assist clinicians in dia...

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

AIM: Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients...

CT Image Analysis and Clinical Diagnosis of New Coronary Pneumonia Based on Improved Convolutional Neural Network.

In this paper, based on the improved convolutional neural network, in-depth analysis of the CT image of the new coronary pneumonia, using the U-Net se...

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the progno...

An Evolutionary Approach for the Enhancement of Dermatological Images and Their Classification Using Deep Learning Models.

Dermatological problems are the most widely spread skin diseases amongst human beings. They can be infectious, chronic, and sometimes may also lead to...

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is d...