AIMC Topic: Treatment Outcome

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Effects of a robot intervention on visuospatial hemineglect in postacute stroke patients: a randomized controlled trial.

Clinical rehabilitation
OBJECTIVE: To evaluate the effects of an intervention using the robot device PARO on visuospatial hemineglect and activities of daily living, and its acceptance during stroke rehabilitation. PARO is an interactive robotic toy with the appearance of a...

Ankle torque steadiness and gait speed after a single session of robot therapy in individuals with chronic hemiparesis: a pilot study.

Topics in stroke rehabilitation
Anklebot therapy has proven to be effective in improving hemiparetic gait. However, neither ankle torque steadiness nor the relationship between changes in force control and functional tasks after therapy with Anklebot were described. To assess whet...

Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial.

Annals of physical and rehabilitation medicine
BACKGROUND: Although gait disorders strongly contribute to perceived disability in people with Parkinson's disease, clinical trials have failed to identify which task-oriented gait training method can provide the best benefit. Freezing of gait remain...

Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.

Pharmacology & therapeutics
A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into e...

Modelling outcomes after paediatric brain injury with admission laboratory values: a machine-learning approach.

Pediatric research
BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of mortality in children, but the accurate prediction of outcomes at the point of admission remains very challenging. Admission laboratory results are a promising potential source of ...

Machine learning methods applied to audit of surgical outcomes after treatment for cancer of the head and neck.

The British journal of oral & maxillofacial surgery
Most surgical specialties have attempted to address concerns about unfair comparison of outcomes by "risk-adjusting" data to benchmark specialty-specific outcomes that are indicative of the quality of care. We are building on previous work in head an...

Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of repeat celiac plexus neurolysis and to build an artificial neural network model able to predict pain ...

An artificial intelligence-based clinical decision support system for large kidney stone treatment.

Australasian physical & engineering sciences in medicine
A decision support system (DSS) was developed to predict postoperative outcome of a kidney stone treatment procedure, particularly percutaneous nephrolithotomy (PCNL). The system can serve as a promising tool to provide counseling before an operation...