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Pathologists

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LLM-based kidney disease diagnostic framework for Pathologists.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Large language models revolutionize the recent paradigm in the medical field and its contributing to various applications, diversified from clinical decision support to information extraction and summarization. The substantial linguistic understandin...

The uropathologist of the future: getting ready with intelligence for the prostate cancer tsunami.

Pathologica
According to the recently published paper by the Lancet Commission on prostate cancer (PCa) , the projections of new cases of PCa will rise from 1.4 million in 2020 to 2.9 million by 2040. Such a rise cannot be prevented by public health intervention...

Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.

Journal of hepatology
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...

The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.

JMIR human factors
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
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 ...

Predicting cancer content in tiles of lung squamous cell carcinoma tumours with validation against pathologist labels.

Computers in biology and medicine
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...

Pathologist-level diagnosis of ulcerative colitis inflammatory activity level using an automated histological grading method.

International journal of medical informatics
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...

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)
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...

Artificial intelligence-enabled histology exhibits comparable accuracy to pathologists in assessing histological remission in ulcerative colitis: a systematic review, meta-analysis, and meta-regression.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Achieving histological remission is a desirable emerging treatment target in ulcerative colitis (UC), yet its assessment is challenging due to high inter- and intraobserver variability, reliance on experts, and lack of standardiz...

A Perspective on Artificial Intelligence for Molecular Pathologists.

The Journal of molecular diagnostics : JMD
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...