AIMC Topic: Male

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Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients.

The Journal of toxicological sciences
Use of laboratory animals for systemic toxicity testing is subject to strong ethical and regulatory constraints, but few alternatives are yet available. One possible approach to predict systemic toxicity of chemicals in the absence of experimental da...

Prediction of brain age suggests accelerated atrophy after traumatic brain injury.

Annals of neurology
OBJECTIVE: The long-term effects of traumatic brain injury (TBI) can resemble observed in normal ageing, suggesting that TBI may accelerate the ageing process. We investigate this using a neuroimaging model that predicts brain age in healthy individu...

An experimental feasibility study on robotic endonasal telesurgery.

Neurosurgery
BACKGROUND: Novel robots have recently been developed specifically for endonasal surgery. They can deliver several thin, tentacle-like surgical instruments through a single nostril. Among the many potential advantages of such a robotic system is the ...

Use of artificial neural networks to predict recurrent lumbar disk herniation.

Journal of spinal disorders & techniques
BACKGROUND: The aim of this study was to develop an artificial neural network (ANN) model to predict recurrent lumbar disk herniation (LDH).

Detection of elevated intracranial pressure in robot-assisted laparoscopic radical prostatectomy using ultrasonography of optic nerve sheath diameter.

Journal of neurosurgical anesthesiology
BACKGROUND: Robot-assisted laparoscopic radical prostatectomy (RALRP) is becoming an increasingly frequent procedure. Pneumoperitoneum and steep trendelenburg positioning associated with this surgery may increase patient's risk for elevated intracran...

Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

European journal of emergency medicine : official journal of the European Society for Emergency Medicine
OBJECTIVE: Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.