AIMC Topic: Humans

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Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

Gene
In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibu...

Bio-inspired deep neural local acuity and focus learning for visual image recognition.

Neural networks : the official journal of the International Neural Network Society
In the field of computer vision and image recognition, enabling the computer to discern target features while filtering out irrelevant ones poses a challenge. Drawing insights from studies in biological vision, we find that there is a local visual ac...

Large Language Model Use in Radiology Residency Applications: Unwelcomed but Inevitable.

Journal of the American College of Radiology : JACR
OBJECTIVE: This study explores radiology program directors' perspectives on the impact of large language model (LLM) use among residency applicants to craft personal statements.

Deep Learning Model for Pathological Grading and Prognostic Assessment of Lung Cancer Using CT Imaging: A Study on NLST and External Validation Cohorts.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a deep learning model for automated pathological grading and prognostic assessment of lung cancer using CT imaging, thereby providing surgeons with a non-invasive tool to guide surgical planning.

ARTIFICIAL INTELLIGENCE IN DENTAL SHADE-MATCHING SHOWS PROMISING POTENTIAL FOR PRECISION IN RESTORATIVE DENTISTRY, THOUGH REQUIRING FURTHER IMPROVEMENT.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Shetty, S., et al. (2023). "Artificial intelligence systems in dental shade-matching: A systematic review." J Prosthodont. DOI: 10.1111/jopr.13805.

Can the preoperative CT-based deep learning radiomics model predict histologic grade and prognosis of chondrosarcoma?

European journal of radiology
BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics...

Artificial intelligence uncertainty quantification in radiotherapy applications - A scoping review.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND/PURPOSE: The use of artificial intelligence (AI) in radiotherapy (RT) is expanding rapidly. However, there exists a notable lack of clinician trust in AI models, underscoring the need for effective uncertainty quantification (UQ) methods. ...

Automated linguistic analysis in youth at clinical high risk for psychosis.

Schizophrenia research
Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to ...

Physiological control for left ventricular assist devices based on deep reinforcement learning.

Artificial organs
BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learn...

A natural language processing-informed adrenal gland incidentaloma clinic improves guideline-based care.

World journal of surgery
INTRODUCTION: Adrenal gland incidentalomas (AGIs) are found in up to 5% of cross-sectional images. However, rates of guideline-based workup for AGIs are notoriously low. We sought to determine if a natural language processing (NLP)-informed AGI clini...