AIMC Topic: Humans

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[Ga]Ga-PSMA-11 PET Tumor Volume Predicts Overall Survival of Patients with Metastatic Prostate Cancer Undergoing Taxane-Based Chemotherapy.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Prostate-specific membrane antigen (PSMA) PET has the potential to monitor the response to taxane-based chemotherapy in patients with prostate cancer and shows promise for predicting outcomes and improving response evaluation. This retrospective stud...

Artificial Intelligence-Powered Quantification of Flortaucipir PET for Detecting Tau Pathology.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
We developed and evaluated an artificial intelligence (AI)-powered approach for easier quantification of tau PET uptake without requiring structural MR to aid earlier tracking of Alzheimer disease (AD). We implemented a deep neural network model tha...

Reimagining cultural heritage conservation through VR, metaverse, and digital twins: An AI and blockchain-based framework.

PloS one
Recent advances in artificial intelligence (AI), blockchain, virtual reality (VR), and digital twin technologies are transforming approaches to cultural heritage conservation. This study develops an integrated analytical framework that combines AI-dr...

Multiview state-of-health estimation for lithium-ion batteries using time-frequency image fusion and attention-based deep learning.

PloS one
Lithium-ion batteries are high-performance energy storage devices that have been widely used in a variety of applications. Accurate early-stage prediction of their remaining useful life is essential for preventing failures and mitigating safety risks...

Diagnosis of colorectal cancer using residual transformer with mixed attention and explainable AI.

PloS one
Colorectal cancer (CRC) is the leading cause of cancer disease and poses a significant threat to global health. Although deep learning models have been utilized to accurately diagnose CRC, they still face challenges in capturing the global correlatio...

Ultraviolet-visible spectral characterization and ANN modeling of aqueous sugar solutions: Clinical and environmental perspectives.

PloS one
The characterization of aqueous sugar solutions using optical techniques offers a non-invasive, rapid, and reagent-free approach for concentration monitoring in both analytical and environmental contexts. In this study, aqueous D-glucose solutions at...

A neural network approach to sarcopenia prediction based on bioelectrical impedance in community-dwelling older adults.

PloS one
This study aimed to apply a neural network to raw bioelectrical impedance analysis data and to test whether sarcopenia could be predicted with high accuracy. The study population comprised 727 community-dwelling older adults aged 65-85 years who part...

Machine learning models for predicting renal injury in patients with gout.

Renal failure
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.

From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy.

World journal of urology
OBJECTIVE: Percutaneous nephrolithotomy is the gold standard for treating large kidney stones. However, traditional scoring systems and logistic regression-based models have limited predictive power due to their reliance on linear assumptions. This s...