AIMC Topic: Pathologists
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Deep learning quantifies pathologists' visual patterns for whole slide image diagnosis.
Nature communications
Jul 1, 2025
Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole slide images (WSI)-assisted diagnostic. However, the collection of pixelwise annotation demands massiv...
Comparative performance of PD-L1 scoring by pathologists and AI algorithms.
Histopathology
Feb 17, 2025
AIM: This study evaluates the comparative effectiveness of pathologists versus artificial intelligence (AI) algorithms in scoring PD-L1 expression in non-small cell lung carcinoma (NSCLC). Immune-checkpoint inhibitors have revolutionized NSCLC treatm...
A Perspective on Artificial Intelligence for Molecular Pathologists.
The Journal of molecular diagnostics : JMD
Feb 13, 2025
The widespread adoption of next-generation sequencing technology in molecular pathology has enabled us to interrogate the genome as never before. The huge quantities of data generated by sequencing, the enormous complexity of human and microbial gene...
Artificial intelligence for diagnosis and predictive biomarkers in Non-Small cell lung cancer Patients: New promises but also new hurdles for the pathologist.
Lung cancer (Amsterdam, Netherlands)
Jan 27, 2025
The rapid development of artificial intelligence (AI) based tools in pathology laboratories has brought forward unlimited opportunities for pathologists. Promising AI applications used for accomplishing diagnostic, prognostic and predictive tasks are...
Predicting cancer content in tiles of lung squamous cell carcinoma tumours with validation against pathologist labels.
Computers in biology and medicine
Dec 4, 2024
BACKGROUND: A growing body of research is using deep learning to explore the relationship between treatment biomarkers for lung cancer patients and cancer tissue morphology on digitized whole slide images (WSIs) of tumour resections. However, these W...
The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.
JMIR human factors
Nov 21, 2024
BACKGROUND: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate ho...
Making Pathologists Ready for the New Artificial Intelligence Era: Changes in Required Competencies.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Nov 13, 2024
In recent years, there has been an increasing interest in developing and using artificial intelligence (AI) models in pathology. Although pathologists generally have a positive attitude toward AI, they report a lack of knowledge and skills regarding ...
Pathologist-level diagnosis of ulcerative colitis inflammatory activity level using an automated histological grading method.
International journal of medical informatics
Oct 9, 2024
BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) is a global disease that is evolving with increasing incidence. However, there are few works on computationally assisted diagnosis of IBD based on pathological images. Therefore, based on the UK a...
Leveraging immuno-fluorescence data to reduce pathologist annotation requirements in lung tumor segmentation using deep learning.
Scientific reports
Sep 16, 2024
The main bottleneck in training a robust tumor segmentation algorithm for non-small cell lung cancer (NSCLC) on H&E is generating sufficient ground truth annotations. Various approaches for generating tumor labels to train a tumor segmentation model ...
Unveiling the risks of ChatGPT in diagnostic surgical pathology.
Virchows Archiv : an international journal of pathology
Sep 13, 2024
ChatGPT, an AI capable of processing and generating human-like language, has been studied in medical education and care, yet its potential in histopathological diagnosis remains unexplored. This study evaluates ChatGPT's reliability in addressing pat...
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