Pathology

Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning.

PURPOSE: To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Endometrial Pipelle Biopsy Computer-Aided Diagnosis: A Feasibility Study.

Endometrial biopsies are important in the diagnostic workup of women who present with abnormal uterine bleeding or hereditary risk of endometrial cancer. In general, approximately 10% of all endometrial biopsies demonstrate endometrial (pre)malignancy that requires specific treatment. As the diagnostic evaluation of mostly benign cases results in a substantial workload for pathologists, artificial...

A computational tumor growth model experience based on molecular dynamics point of view using deep cellular automata.

Cancer, as identified by the World Health Organization, stands as the second leading cause of death globally. Its intricate nature makes it challengin...

Exploring the infiltrative and degradative ability of Fusarium oxysporum on polyethylene terephthalate (PET) using correlative microscopy and deep learning.

Managing the worldwide steady increase in the production of plastic while mitigating the Earth's global pollution is one of the greatest challenges no...

First Record of Microplastic Contamination in the Non-Native Dark False Mussel (Bivalvia: Dreissenidae) in a Coastal Urban Lagoon.

Microplastic contamination is a global concern due to its conspicuous presence in aquatic ecosystems and its toxic nature to environmental and human h...

Treatment prediction with machine learning in prostate cancer patients.

There are various treatment modalities for prostate cancer, which has a high incidence. In this study, it is aimed to make predictions with machine le...

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update.

Significant advances in artificial intelligence (AI) over the past decade potentially may lead to dramatic effects on clinical practice. Digitized his...

Gynecologic Surgical Subspecialty Training Decreases Surgical Complications in Benign Minimally Invasive Hysterectomy.

STUDY OBJECTIVE: To evaluate the impact of gynecologic subspecialty training on surgical outcomes in benign minimally invasive hysterectomies (MIHs) w...

Robot-assisted resection of benign splenic tumors in children.

PURPOSE: Robotic surgery is becoming increasingly widely used in the field of pediatric surgery. The present study aimed to evaluate the safety and fe...

Leveraging Interpretable Feature Representations for Advanced Differential Diagnosis in Computational Medicine.

Diagnostic errors represent a critical issue in clinical diagnosis and treatment. In China, the rate of misdiagnosis in clinical diagnostics is approx...

Machine Learning Combined with Radiomics Facilitating the Personal Treatment of Malignant Liver Tumors.

In the realm of managing malignant liver tumors, the convergence of radiomics and machine learning has redefined the landscape of medical practice. Th...

Unlocking Early Cancer Detection: Exploring Biomarkers, Circulating DNA, and Innovative Technological Approaches.

Research and development improvements in early cancer diagnosis have had a significant positive impact on health. In the treatment and prevention of c...

Electroglottography in Medical Diagnostics of Vocal Tract Pathologies: A Systematic Review.

Electroglottography (EGG) is a technology developed for measuring the vocal fold contact area during human voice production. Although considered subje...

The future of digital cytology and artificial intelligence: an editorial commentary for Digital Cytology part 1 and 2.

Robotic Microsurgery in Extremity Reconstruction - Experience With a Novel Robotic System.

Robotic systems have successfully been introduced into other surgical fields in the past. First attempts with different setups are made in the field ...

Quality control in clinical raster-scan optoacoustic mesoscopy.

Optoacoustic (photoacoustic) mesoscopy bridges the gap between optoacoustic microscopy and macroscopy and enables high-resolution visualization deeper...

Optical imaging for screening and early cancer diagnosis in low-resource settings.

Low-cost optical imaging technologies have the potential to reduce inequalities in healthcare by improving the detection of pre-cancer or early cancer...

Learning image representations for anomaly detection: Application to discovery of histological alterations in drug development.

We present a system for anomaly detection in histopathological images. In histology, normal samples are usually abundant, whereas anomalous (pathologi...

Deep learning framework for automated goblet cell density analysis in in-vivo rabbit conjunctiva.

Goblet cells (GCs) in the conjunctiva are specialized epithelial cells secreting mucins for the mucus layer of protective tear film and playing immune...

Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images.

Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized g...