AIMC Topic: Treatment Outcome

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Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.

Medical physics
PURPOSE: There has been burgeoning interest in applying machine learning methods for predicting radiotherapy outcomes. However, the imbalanced ratio of a large number of variables to a limited sample size in radiation oncology constitutes a major cha...

Oncologic outcomes in patients treated with endoscopic robot assisted simple enucleation (ERASE) for renal cell carcinoma: Results from a tertiary referral center.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Open Simple Enucleation (OSE) has been demonstrated to be an oncologically safe alternative to standard partial nephrectomy. We assessed the mid-term oncologic outcomes and predictors of disease recurrence in patients treated with Endos...

Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy.

PloS one
Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imagin...

Effects of robotic rehabilitation on walking and balance in pediatric patients with hemiparetic cerebral palsy.

Gait & posture
BACKGROUND: The most prominent characteristics of hemiparetic cerebral palsy (hCP) children are structural and functional asymmetries. These children have low walking speeds, endurance and poor balance. The robotic walking devices repeat and experien...

An artificial neural network model for prediction of hypoxemia during sedation for gastrointestinal endoscopy.

The Journal of international medical research
OBJECTIVE: This study was designed to assess clinical predictors of hypoxemia and develop an artificial neural network (ANN) model for prediction of hypoxemia during sedation for gastrointestinal endoscopy examination.

Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants.

World neurosurgery
BACKGROUND: Cervical spondylotic myelopathy (CSM) severity and presence of symptoms are often difficult to predict based simply on clinical imaging alone. Similarly, improved machine learning techniques provide new tools with immense clinical potenti...