AIMC Topic: Humans

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Refractive outcomes of second-eye adjustment methods on intraocular lens power calculation in second eye.

Clinical & experimental ophthalmology
BACKGROUND: To investigate the refractive outcomes of second-eye adjustment (SEA) methods in different intraocular lens (IOL) power calculation formulas for second eye following bilateral sequential cataract surgery.

A disease-specific language representation model for cerebrovascular disease research.

Computer methods and programs in biomedicine
BACKGROUND: Effectively utilizing disease-relevant text information from unstructured clinical notes for medical research presents many challenges. BERT (Bidirectional Encoder Representation from Transformers) related models such as BioBERT and Clini...

Breast nodule classification with two-dimensional ultrasound using Mask-RCNN ensemble aggregation.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to create a deep learning algorithm to infer the benign or malignant nature of breast nodules using two-dimensional B-mode ultrasound data initially marked as BI-RADS 3 and 4.

A deep learning approach for real-time crash prediction using vehicle-by-vehicle data.

Accident; analysis and prevention
In road safety, real-time crash prediction may play a crucial role in preventing such traffic events. However, much of the research in this line generally uses data aggregated every five or ten minutes. This article proposes a new image-inspired data...

Evaluation and Real-World Performance Monitoring of Artificial Intelligence Models in Clinical Practice: Try It, Buy It, Check It.

Journal of the American College of Radiology : JACR
The pace of regulatory clearance of artificial intelligence (AI) algorithms for radiology continues to accelerate, and numerous algorithms are becoming available for use in clinical practice. End users of AI in radiology should be aware that AI algor...

Robustness of deep learning segmentation of cardiac substructures in noncontrast computed tomography for breast cancer radiotherapy.

Medical physics
PURPOSE: To develop and evaluate deep learning-based autosegmentation of cardiac substructures from noncontrast planning computed tomography (CT) images in patients undergoing breast cancer radiotherapy and to investigate the algorithm sensitivity to...

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

The British journal of radiology
At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk-benefit ratio...

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy options for T1 lung adenocarcinoma patients. Radiologists preoperatively diagnose LN metastasis by evaluating signs related to LN metastasis, like spicul...

Perioperative outcomes of intracorporeal robot-assisted radical cystectomy versus open radical cystectomy: A systematic review and meta-analysis of comparative studies.

International journal of surgery (London, England)
PURPOSE: To systematically review studies comparing the perioperative outcomes of intracorporeal robot-assisted radical cystectomy (iRARC) and open radical cystectomy (ORC).

IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound.

IEEE transactions on medical imaging
We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle...