AIMC Topic: Aged

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Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network.

Scientific reports
Endometrial cancer (EC) is the most common gynecological tumor in developed countries, and preoperative risk stratification is essential for personalized medicine. There have been several radiomics studies for noninvasive risk stratification of EC us...

Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases.

Scientific reports
Tumor types are classically distinguished based on biopsies of the tumor itself, as well as a radiological interpretation using diverse MRI modalities. In the current study, the overarching goal is to demonstrate that primary (glioblastomas) and seco...

Deep Learning on MRI Images for Diagnosis of Lung Cancer Spinal Bone Metastasis.

Contrast media & molecular imaging
This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer...

Use of Deep-Learning Genomics to Discriminate Healthy Individuals from Those with Alzheimer's Disease or Mild Cognitive Impairment.

Behavioural neurology
OBJECTIVES: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Certain genes have been identified as important clinical risk factors for AD, and technological advances in gen...

Predicting self-intercepted medication ordering errors using machine learning.

PloS one
Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to mis...

Robotic guidance platform for laser interstitial thermal ablation and stereotactic needle biopsies: a single center experience.

Journal of robotic surgery
While laser ablation has become an increasingly important tool in the neurosurgical oncologist's armamentarium, deep seated lesions, and those located near critical structures require utmost accuracy during stereotactic laser catheter placement. Robo...

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

Clinical breast cancer
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

The Journal of investigative dermatology
Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied ...

Exoskeleton robots for lower limb assistance: A review of materials, actuation, and manufacturing methods.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The field of robot-assisted physical rehabilitation and robotics technology for providing support to the elderly population is rapidly evolving. Lower limb robot aided rehabilitation and assistive technology have been a focus for the engineering comm...

Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study.

Journal of Korean medical science
BACKGROUND: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed ...