AIMC Topic: Humans

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Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

Journal of the American College of Radiology : JACR
OBJECTIVE: Legislation in 38 states requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit mammographic sensitivity. Because radiologist density assessments vary wid...

Short report: surgery for implantable brain-computer interface assisted by robotic navigation system.

Acta neurochirurgica
We present an implantable brain-computer interface surgical case assisted by robotic navigation system in an elderly patient with tetraplegia caused by cervical spinal cord injury. Left primary motor cortex was selected for implantation of microelect...

Deep learning-based classification of DSA image sequences of patients with acute ischemic stroke.

International journal of computer assisted radiology and surgery
PURPOSE: Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention technique for mechanically removing thrombi from the cerebrovasculature. During thrombectomy, 2D digita...

Trends and factors affecting approach choice to pulmonary resection.

Journal of surgical oncology
BACKGROUND: The development of an advanced robotic platform in 2014 led to increased adoption of minimally invasive (MI) approaches in thoracic surgery. Due to dataset reporting lag, a comprehensive assessment of trends in thoracic approaches has not...

A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery.

Dento maxillo facial radiology
Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventions and has therefore become an increasingly popular treatment modality in maxillofacial surgery. The current maxillofacial CAS consists of three main ...

A classification for complex imbalanced data in disease screening and early diagnosis.

Statistics in medicine
Imbalanced classification has drawn considerable attention in the statistics and machine learning literature. Typically, traditional classification methods often perform poorly when a severely skewed class distribution is observed, not to mention und...

Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
AIM: To train and validate a comprehensive deep-learning (DL) segmentation model for loco-regional breast cancer with the aim of clinical implementation.

A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma based on endoscopic images using deep learning.

The British journal of radiology
OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images.

A Deep Learning Model for Accurate Diagnosis of Infection Using Antibody Repertoires.

Journal of immunology (Baltimore, Md. : 1950)
The adaptive immune receptor repertoire consists of the entire set of an individual's BCRs and TCRs and is believed to contain a record of prior immune responses and the potential for future immunity. Analyses of TCR repertoires via deep learning (DL...