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The evolution of pathology from its rudimentary beginnings around 1700 BC to the present day has been marked by profound advancement in understanding and diagnosing diseases. This journey, from the earliest dissections to the modern era of histochemical analysis, sets the stage for the next transformative leap to the integration of artificial intelligence (AI) in pathology. Recent research highlights AI's significant potential to revolutionize healthcare within the next decade, with a particular impact on diagnostic processes. A majority of pathologists foresee AI becoming a cornerstone in diagnostic workflow, driven by the advent of image-based algorithms and computational pathology. These innovations promise to enhance the precision of disease diagnosis, particularly in complex cases, such as cancers, by offering detailed insights into the molecular and cellular mechanisms. Moreover, AI-assisted tools are improving the efficiency and accuracy of histological analysis by automating the evaluation of immunohistochemical biomarkers and tissue architecture. This shift not only accelerates diagnostic processes but also facilitates early disease management, crucial for improving patient outcomes. Furthermore, AI is reshaping educational paradigms in pathology, offering interactive learning environments that promise to enrich the training of future pathologists. Despite these advancements, the integration of AI in pathology raises ethical considerations regarding patient consent and data privacy. As pathology embarks on this AI-augmented era, it is imperative to navigate these challenges thoughtfully, ensuring that AI enhances rather than replaces the pathologist's role. This editorial discussed the historical progression of pathology, the current impact of AI on diagnostic practices, and the ethical implications of its adoption, underscoring the need for a symbiotic relationship between pathologists and AI to unlock the full potential of healthcare.
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http://dx.doi.org/10.7759/cureus.56040 | DOI Listing |
Biom J
October 2025
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Accelerated failure time (AFT) models offer an attractive alternative to Cox proportional hazards models. AFT models are collapsible and, unlike hazard ratios in proportional hazards models, the acceleration factor-a key effect measure in AFT models-is collapsible, meaning its value remains unchanged when adjusting for additional covariates. In addition, AFT models provide an intuitive interpretation directly on the survival time scale.
View Article and Find Full Text PDFActa Neuropathol Commun
September 2025
Department of Biomedical and Clinical Sciences and Department of Clinical Pathology, Linköping University, 58185, Linköping, Sweden.
Disruptions in synaptic transmission and plasticity are early hallmarks of Alzheimer's disease (AD). Endosomal trafficking, mediated by the retromer complex, is essential for intracellular protein sorting, including the regulation of amyloid precursor protein (APP) processing. The VPS35 subunit, a key cargo-recognition component of the retromer, has been implicated in neurodegenerative diseases, with mutations such as L625P linked to early-onset AD.
View Article and Find Full Text PDFLab Anim Res
September 2025
Department of Pathology, Faculty of Medicine, Kindai University, 377-2 Ohno-Higashi, Osaka-Sayama, Osaka, 589-8511, Japan.
Background: Stroke-prone spontaneously hypertensive rats (SHRSP) exhibit slow-twitch muscle-specific hypotrophy compared with normotensive Wistar-Kyoto rats (WKY). Because slow-twitch muscles are prone to disuse atrophy, SHRSP may experience both disuse atrophy and impaired recovery from it. This study investigated the response of SHRSP to disuse atrophy and subsequent recovery, using WKY as a control.
View Article and Find Full Text PDFBMC Med Educ
September 2025
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.
Background: Health professions students may encounter a range of stressors during their clinical education that may impact their quality of life. This study aimed to explore how various health professions students perceive their quality of life and the environment in which they develop their clinical skills.
Methods: An online survey was administered among registered undergraduate students in the physiotherapy, speech-language pathology, nursing, or medical programs.
Int J Lab Hematol
September 2025
Department of Hematology, Tongde Hospital of Zhejiang Province, Hangzhou, China.
Background: T follicular helper (TFH) cell lymphoma is complex, and we hope to provide a new perspective for its diagnosis.
Methods: We analysed the immunophenotypes of 89 mature T-cell lymphomas, including 52 nodal lymphomas of TFH origin, as well as 32 benign lymph node samples and 30 healthy bone marrow samples, by flow cytometry (FCM).
Results: Among pan-T cell markers, CD4CD5CD3 is the typical pattern that distinguishes TFH lymphoma from other T-cell lymphomas.