AIMC Topic: Adult

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Preoperative prediction of regional lymph node metastasis of colorectal cancer based on F-FDG PET/CT and machine learning.

Annals of nuclear medicine
PURPOSE: To establish and validate a regional lymph node (LN) metastasis prediction model of colorectal cancer (CRC) based on F-FDG PET/CT and radiomic features using machine-learning methods.

Development and Validation of a Deep Learning-Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Differentiating glioblastoma from solitary brain metastasis preoperatively using conventional MR images is challenging. Deep learning models have shown promise in performing classification tasks. The diagnostic performance of ...

Assessment of medication self-administration using artificial intelligence.

Nature medicine
Errors in medication self-administration (MSA) lead to poor treatment adherence, increased hospitalizations and higher healthcare costs. These errors are particularly common when medication delivery involves devices such as inhalers or insulin pens. ...

Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

PloS one
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with h...

Deep Learning to Estimate Biological Age From Chest Radiographs.

JACC. Cardiovascular imaging
OBJECTIVES: The goal of this study was to assess whether a deep learning estimate of age from a chest radiograph image (CXR-Age) can predict longevity beyond chronological age.

Deep learning based segmentation of brain tissue from diffusion MRI.

NeuroImage
Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weigh...

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Human brain mapping
Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we ...

Predicting Age Groups of Reddit Users Based on Posting Behavior and Metadata: Classification Model Development and Validation.

JMIR public health and surveillance
BACKGROUND: Social media are important for monitoring perceptions of public health issues and for educating target audiences about health; however, limited information about the demographics of social media users makes it challenging to identify conv...

Expanding TNM for lung cancer through machine learning.

Thoracic cancer
BACKGROUND: Expanding the tumor, lymph node, metastasis (TNM) staging system by accommodating new prognostic and predictive factors for cancer will improve patient stratification and survival prediction. Here, we introduce machine learning for incorp...