Pathology

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

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Multimodal Artificial Intelligence-Based Virtual Biopsy for Diagnosing Abdominal Lavage Cytology-Positive Gastric Cancer.

Gastric cancer with peritoneal dissemination remains a significant clinical challenge due to its poo...

Content-Based Histopathological Image Retrieval.

Feature descriptors in histopathological images are an important challenge for the implementation of...

Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation.

Pathologists have depended on their visual experience to assess tissue structures in smear images, w...

Improving Malaria diagnosis through interpretable customized CNNs architectures.

Malaria, which is spread via female Anopheles mosquitoes and is brought on by the Plasmodium parasit...

Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery.

PURPOSE: Several surgical-skill assessment tools emphasize the importance of efficient tissue-dissec...

AI-augmented Biophysical modeling in thermoplasmonics for real-time monitoring and diagnosis of human tissue infections.

Identifying tissue infections from the body still poses an unprecedented challenge in society. Conve...

Optimizing thermal dose prediction in nanoparticle-mediated photothermal therapy using a convolutional neural network-based model.

Nanoparticle-mediated photothermal therapy (NMPTT) is an up-and-coming targeted cancer treatment. He...

Raman spectroscopy for colorectal tumor margin assessment: A promising tool for real-time surgical delimitation.

Raman spectroscopy is a promising non-invasive technique not only for the rapid and accurate detecti...

Towards precision medicine strategies using plasma proteomic profiling for suspected gallbladder cancer: A pilot study.

BACKGROUND & AIMS: Currently, preoperative diagnostic methods that can distinguish cancer from benig...

Enhancing diagnostic accuracy of thyroid nodules: integrating self-learning and artificial intelligence in clinical training.

PURPOSE: This study explores a self-learning method as an auxiliary approach in residency training f...

TRUSWorthy: toward clinically applicable deep learning for confident detection of prostate cancer in micro-ultrasound.

PURPOSE: While deep learning methods have shown great promise in improving the effectiveness of pros...

Pathology-based deep learning features for predicting basal and luminal subtypes in bladder cancer.

BACKGROUND: Bladder cancer (BLCA) exists a profound molecular diversity, with basal and luminal subt...

Reliability of noninvasive hyperspectral tongue diagnosis for menstrual diseases using machine learning method.

The outward appearance of human tongue can reflect changes in blood circulation caused by pathologic...

Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [F]PSMA-1007 PET/CT and multiparametric MRI.

PURPOSE: Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial ...

Long-tailed medical diagnosis with relation-aware representation learning and iterative classifier calibration.

Recently computer-aided diagnosis has demonstrated promising performance, effectively alleviating th...

Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.

Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely dia...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for p...

Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data.

A brain tumor is an abnormal growth of cells within the brain or surrounding tissues, which can be e...

Assessment of AI-based computational H&E staining versus chemical H&E staining for primary diagnosis in lymphomas: a brief interim report.

Microscopic review of tissue sections is of foundational importance in pathology, yet the traditiona...

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