AIMC Topic: Artificial Intelligence

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Development and Validation of a Deep Learning-Based Histologic Diagnosis System for Diagnosing Colorectal Sessile Serrated Lesions.

American journal of clinical pathology
OBJECTIVES: The histopathologic diagnosis of colorectal sessile serrated lesions (SSLs) and hyperplastic polyps (HPs) is of low consistency among pathologists. This study aimed to develop and validate a deep learning (DL)-based logical anthropomorphi...

Introducing the 's policy on the use of generative artificial intelligence in submissions.

Journal of the Medical Library Association : JMLA
With the arrival of ChatGPT, the academic community has expressed concerns about how generative artificial intelligence will be used by students and researchers alike. After consulting policies from other journals and discussing among the editorial t...

[Comparative analysis of two assaysin detection of sperm DNA fragmentation index, flow cytometry and AI-based fluorescence microscopy, based on AO staining: A multicentre study].

Zhonghua nan ke xue = National journal of andrology
OBJECTIVE: To study the correlation, consistency, and variations between two assays of DNA fragmentation index based on acridine orange (AO) staining via AI-based fluorescence microscopy(AI-DFI), and flow cytometry (FCM-DFI) across multiple centers.

Unveiling the power of convolutional neural networks in melanoma diagnosis.

European journal of dermatology : EJD
Convolutional neural networks are a type of deep learning algorithm. They are mostly applied in visual recognition and can be used for the identification of melanomas. Multiple studies have evaluated the performance of convolutional neural networks, ...

Comparison of wound surface area measurements obtained using clinically validated artificial intelligence-based technology versus manual methods and the effect of measurement method on debridement code reimbursement cost.

Wounds : a compendium of clinical research and practice
BACKGROUND: Evidence shows that ongoing accurate wound assessments using valid and reliable measurement methods is essential to effective wound monitoring and better wound care management. Relying on subjective interpretation in measuring wound dimen...

A systematic review of artificial intelligence algorithms for predicting acute kidney injury.

European review for medical and pharmacological sciences
OBJECTIVE: Acute kidney injury (AKI) increases mortality and costs in hospitalized patients. New methods for early AKI identification have been developed with targeted biomarkers and electronic health records data analysis. Machine learning (ML) use ...

Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting.

Radiology
Background Most artificial intelligence algorithms that interpret chest radiographs are restricted to an image from a single time point. However, in clinical practice, multiple radiographs are used for longitudinal follow-up, especially in intensive ...