Pathology

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

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BSA-Seg: A Bi-level sparse attention network combining narrow band loss for multi-target medical image segmentation.

Segmentation of multiple targets of varying sizes within medical images is of significant importance...

Dataset of compression after impact testing on carbon fiber reinforced plastic laminates.

This dataset covers the data obtained from the compression after impact (CAI) tests. Before the CAI ...

A lightweight PCT-Net for segmenting neural fibers in low-quality CCM images.

In this paper, we propose a lightweight Position Channel Transformer Network (PCT-Net) for segmentin...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamo...

High-resolution ultrasound of the annular pulley system in the toes: sonographic anatomy and pathological cases.

OBJECTIVE: To validate high-frequency ultrasound as a valuable imaging modality in the assessment of...

Structure information preserving domain adaptation network for fault diagnosis of Sucker Rod Pumping systems.

Fault diagnosis is of great importance to the reliability and security of Sucker Rod Pumping (SRP) o...

On the use of a Transformer Neural Network to deconvolve ultrasonic signals.

Pulse-echo ultrasonic techniques play a crucial role in assessing wall thickness deterioration in sa...

GeNIS: A modular dataset for network intrusion detection and classification.

The development of artificial intelligence solutions for cyberattack detection and classification re...

HistoMSC: Density and topology analysis for AI-based visual annotation of histopathology whole slide images.

We introduce an end-to-end framework for the automated visual annotation of histopathology whole sli...

SegElegans: Instance segmentation using dual convolutional recurrent neural network decoder in Caenorhabditis elegans microscopic images.

Caenorhabditis elegans is a great model for exploring organismal, cellular, and subcellular biology ...

Thinking Like Sonographers: Human-Centered CNN Models for Gout Diagnosis From Musculoskeletal Ultrasound.

We explore the potential of deep convolutional neural network (CNN) models for differential diagnosi...

Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.

Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The im...

Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion.

Malignant pleural effusion (MPE) is a common complication in patients with advanced lung cancer, sig...

Transforming neurodegenerative disorder care with machine learning: Strategies and applications.

Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting...

AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines.

BACKGROUND: Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with va...

Development of PDAC diagnosis and prognosis evaluation models based on machine learning.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and highly aggressi...

A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation.

Colorectal cancer (CRC) is a prevalent gastrointestinal tumor worldwide with high morbidity and mort...

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