AIMC Topic: Humans

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An innovative approach for predicting prostate cancer Gleason grading: machine learning-based fusion of multimodal ultrasound, clinical and laboratory indicators.

European journal of medical research
BACKGROUND: Prostate cancer is a common malignancy among elderly males with a growing incidence. While prostate biopsy remains the gold standard for diagnosis, this invasive procedure is poorly tolerated by some patients. The Gleason grade group (GGG...

Utility and Limitations of Large Language Models to Simplify Online Content on Generalized Pustular Psoriasis.

Rhode Island medical journal (2013)
Online health information (OHI) in dermatology often exceeds the recommended sixth-grade reading level, hindering patient comprehension. This study aimed to assess the utility of three artificial intelligence large language models (LLMs) - ChatGPT-3....

Iterative improvement of deep learning models using synthetic regulatory genomics.

Genome research
Deep learning models can accurately reconstruct genome-wide epigenetic tracks from the reference genome sequence alone. But it is unclear what predictive power they have on sequence diverging from the reference, such as disease- and trait-associated ...

MRI-Based Quantification of Intratumoral Heterogeneity for Predicting Progression-Free Survival in Patients with Lung Cancer Brain Metastasis Receiving Radiotherapy.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Our aim was to investigate the potential of using MRI-based habitat features for predicting progression-free survival (PFS) in patients with lung cancer brain metastasis (LCBM) receiving radiotherapy.

Three-dimensional ultrasound imaging: a review of the technology.

Physics in medicine and biology
Three-dimensional (3D) ultrasound imaging is now established across a wide range of clinical applications, offering real-time volumetric visualisation of anatomical structures while remaining low-cost, portable, and non-ionising. This topical review ...

Prediction of clinical outcomes of ST-elevated myocardial infarction patients using atmospheric solids analysis probe mass spectrometry and machine learning.

The Analyst
: Analysis of small molecule metabolites found in blood plasma of patients undergoing treatment for STEMI has the potential to be used as a clinical diagnostic and prognostic tool, capable of predicting disease progression, risk of negative outcomes,...

Prognostic Value of AI-Assisted Lesion Tracking on End-of-Treatment PSMA PET in mCRPC Patients Treated with Lu-PSMA: A Retrospective, Single-Center Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
This study aimed to explore the prognostic value of the artificial intelligence-assisted lesion tracking applied to prostate-specific membrane antigen (PSMA) PET in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with PS...

Deep structural clustering reveals hidden systematic biases in RNA sequencing data.

Genome research
RNA sequencing (RNA-seq) is a pivotal tool for transcriptomic analysis, providing comprehensive exploration of gene expression across diverse biological contexts. However, RNA-seq data are susceptible to various biases that can significantly compromi...

Deep Learning for Automated Measures of SUV and Molecular Tumor Volume in [Ga]PSMA-11 or [F]DCFPyL, [F]FDG, and [Lu]Lu-PSMA-617 Imaging with Global Threshold Regional Consensus Network.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Metastatic castration-resistant prostate cancer has a high rate of mortality with a limited number of effective treatments after hormone therapy. Radiopharmaceutical therapy with [Lu]Lu-prostate-specific membrane antigen-617 (LuPSMA) is one treatment...

Fully Automated Image-Based Multiplexing of Serial PET/CT Imaging for Facilitating Comprehensive Disease Phenotyping.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Combined PET/CT imaging provides critical insights into both anatomic and molecular processes, yet traditional single-tracer approaches limit multidimensional disease phenotyping; to address this, we developed the PET Unified Multitracer Alignment (P...