AIMC Topic: Humans

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Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

Journal of neurosurgery
OBJECTIVE: It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly ...

Evaluation of aesthetic outcomes of mandibular reconstruction using artificial intelligence.

Head & neck
BACKGROUND: Although vascularized bone graft (VBG) transfer is the current standard for mandibular reconstruction, reconstruction with a mandibular reconstruction plate (MRP) and with a soft-tissue flap (STF) alone remain crucial options for patients...

Deep Learning Radiomics Model of Contrast-Enhanced CT for Differentiating the Primary Source of Liver Metastases.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CT) to identify the primary source of liver metastases.

Assessing Endoscopic Response in Locally Advanced Rectal Cancer Treated with Total Neoadjuvant Therapy: Development and Validation of a Highly Accurate Convolutional Neural Network.

Annals of surgical oncology
BACKGROUND: Rectal tumors display varying degrees of response to total neoadjuvant therapy (TNT). We evaluated the performance of a convolutional neural network (CNN) in interpreting endoscopic images of either a non-complete response to TNT or local...

Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (IgG4-ROD) and orbital MALT lymphoma using artificial intelligence (AI) and hematoxylin-eosin (HE) images.

Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

ESC heart failure
AIMS: Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. ...

A robust self-supervised image hashing method for content identification with forensic detection of content-preserving manipulations.

Neural networks : the official journal of the International Neural Network Society
Image content identification systems have many applications in industry and academia. In particular, a hash-based content identification system uses a robust image hashing function that computes a short binary identifier summarizing the perceptual co...

Decoding medical jargon: The use of AI language models (ChatGPT-4, BARD, microsoft copilot) in radiology reports.

Patient education and counseling
OBJECTIVE: Evaluate Artificial Intelligence (AI) language models (ChatGPT-4, BARD, Microsoft Copilot) in simplifying radiology reports, assessing readability, understandability, actionability, and urgency classification.

The role of AI and machine learning in the diagnosis of Parkinson's disease and atypical parkinsonisms.

Parkinsonism & related disorders
Parkinson's disease is a neurodegenerative movement disorder associated with motor and non-motor symptoms causing severe disability as the disease progresses. The development of biomarkers for Parkinson's disease to diagnose patients earlier and pred...