Pathology

Latest AI and machine learning research in pathology for healthcare professionals.

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Annotation Practices in Computational Pathology: A European Society of Digital and Integrative Pathology (ESDIP) Survey Study.

Integrating digital pathology and artificial intelligence (AI) algorithms can potentially improve di...

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models.

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hype...

Prediction model for ocular metastasis of breast cancer: machine learning model development and interpretation study.

BACKGROUND: Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cell...

Classification of melanoma skin Cancer based on Image Data Set using different neural networks.

This paper aims to address the pressing issue of melanoma classification by leveraging advanced neur...

Pediatric Liver Transplant Pathology: An Update and Practical Consideration.

This review provides a summary of the diagnostic approach to pediatric liver transplantation (LT) pa...

Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.

The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the ex...

FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification.

Histopathological tissue classification is a fundamental task in computational pathology. Deep learn...

Role of Artificial Intelligence for Colon Polyp Detection and Diagnosis and Colon Cancer.

The broad use of artificial intelligence (AI) and its various applications have already shown signif...

A Predictive Model Integrating AI Recognition Technology and Biomarkers for Lung Nodule Assessment.

BACKGROUND:  Lung cancer is the most prevalent and lethal cancer globally, necessitating accurate di...

Advancing Laboratory Medicine Practice With Machine Learning: Swift yet Exact.

Machine learning (ML) is currently being widely studied and applied in data analysis and prediction ...

Virtual histopathology methods in medical imaging - a systematic review.

Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computati...

Measuring Metabolic Changes in Cancer Cells Using Two-Photon Fluorescence Lifetime Imaging Microscopy and Machine-Learning Analysis.

Two-photon (2P) fluorescence lifetime imaging microscopy (FLIM) was used to track cellular metabolis...

An Application of Machine-Learning-Oriented Radiomics Model in Clear Cell Renal Cell Carcinoma (ccRCC) Early Diagnosis.

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of kidney cancer, where ear...

An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning.

Ultrasonography (US) of thyroid nodules is often time consuming and may be inconsistent between obse...

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using ches...

Image-based Artificial Intelligence models in the diagnosis and classification of vascular anomalies of the soft tissue in the head and neck.

BACKGROUND: The International Society for the Study of Vascular Anomalies (ISSVA) provides a detaile...

The potential of AI-assisted gastrectomy with dual highlighting of pancreas and connective tissue.

BACKGROUND: Standard gastrectomy with D2 lymph node (LN) dissection for gastric cancer involves peri...

A deep neural network improves endoscopic detection of laterally spreading tumors.

BACKGROUND: Colorectal cancer (CRC) is the malignant tumor of the digestive system with the highest ...

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