Dermatology

Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs: Case-control study.

Along with recent developments in deep learning techniques, computer-aided diagnosis (CAD) has been ...

New international reporting guidelines for clinical trials evaluating effectiveness of artificial intelligence interventions in dermatology: strengthening the SPIRIT of robust trial reporting.

The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.

Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive acc...

Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images.

A reported 96,480 people were diagnosed with melanoma in the United States in 2019, leading to 7230 ...

Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma.

Differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma (ML) remains cha...

Role of Intralesional Vitamin D3 in the Treatment of Cutaneous Warts.

BACKGROUND: Cutaneous warts are common benign skin lesions caused by human papillomavirus. Various t...

Xanthatin Induces Leishmanicidal Activity by Affecting Carbon Metabolism in Amastigotes.

Cutaneous leishmaniasis is caused by protozoa of the genus and spread by sandflies. The standard th...

[A Study on Radiation Dermatitis Grading Support System Based on Deep Learning by Hybrid Generation Method].

PURPOSE: Radiation dermatitis is one of the most common adverse events in patients undergoing radiot...

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important too...

Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain ...

In-Cell Single-Molecule Analysis of Molecular State and Reaction Kinetics Coupling.

Cellular signaling is regulated by the spatiotemporal dynamics and kinetics of molecular behavior. T...

Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Deep learning algorithms have shown excellent performances in the field of medical image recognition...

A Case of Dapsone-induced Mild Methemoglobinemia with Dyspnea and Cyanosis.

Dear Editor, Dapsone is a dual-function drug with antimicrobial and antiprotozoal effects and anti-i...

Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple ...

Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

BACKGROUND: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired d...

Multiclass retinal disease classification and lesion segmentation in OCT B-scan images using cascaded convolutional networks.

Disease classification and lesion segmentation of retinal optical coherence tomography images play i...

Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma.

IMPORTANCE: Less than 10% of patients with cancer have detectable pathogenic germline alterations, w...

[Determination of dacarbazine in the urine of mice with melanoma by high performance liquid chromatography].

Dacarbazine (DTIC) is a first-line chemotherapy drug that is widely used in clinical practice for ma...

Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.

SIGNIFICANCE: Melanoma is a deadly cancer that physicians struggle to diagnose early because they la...

Deep learning-based, computer-aided classifier developed with dermoscopic images shows comparable performance to 164 dermatologists in cutaneous disease diagnosis in the Chinese population.

BACKGROUND: Diagnoses of Skin diseases are frequently delayed in China due to lack of dermatologists...

Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints.

Artificial intelligence (AI) is a disruptive technology that involves the use of computerised algori...