AI Medical Compendium Topic:
Pilot Projects

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Utility of deep neural networks in predicting gross-total resection after transsphenoidal surgery for pituitary adenoma: a pilot study.

Neurosurgical focus
OBJECTIVEGross-total resection (GTR) is often the primary surgical goal in transsphenoidal surgery for pituitary adenoma. Existing classifications are effective at predicting GTR but are often hampered by limited discriminatory ability in moderate ca...

Deep Learning-Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study.

Thyroid : official journal of the American Thyroid Association
BACKGROUND: The presence of metastatic lymph nodes is a prognostic indicator for patients with thyroid carcinomas and is an important determinant of clinical decision making. However, evaluating neck lymph nodes requires experience and is labor- and ...

Effects of newly developed compact robot-aided upper extremity training system (Neuro-X®) in patients with stroke: A pilot study.

Journal of rehabilitation medicine
OBJECTIVE: Robot-assisted rehabilitation therapy of the upper extremity after stroke has been studied widely; however, robotic devices remain expensive and bulky. The aim of this study was to evaluate the effects of a newly developed, compact upper e...

Predict In-Hospital Code Blue Events using Monitor Alarms through Deep Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Bedside monitors in hospital intensive care units (ICUs) are known to produce excessive false alarms that could desensitize caregivers, resulting in delayed or even missed clinical interventions to life-threatening events. Our previous studies propos...

Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods.

Medicine and science in sports and exercise
PURPOSE: This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data.

Detection of high-grade small bowel obstruction on conventional radiography with convolutional neural networks.

Abdominal radiology (New York)
The purpose of this pilot study is to determine whether a deep convolutional neural network can be trained with limited image data to detect high-grade small bowel obstruction patterns on supine abdominal radiographs. Grayscale images from 3663 clini...

Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

Journal of diabetes science and technology
BACKGROUND: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabet...

Effects of integrating rhythmic arm swing into robot-assisted walking in patients with subacute stroke: a randomized controlled pilot study.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
This study aimed to identify the effects of rhythmic arm swing during robot-assisted walking training on balance, gait, motor function, and activities of daily living among patients with subacute stroke. Twenty patients with subacute stroke were recr...