Fee comparisons of treatments for nonmelanoma skin cancer in a private practice academic setting.

Objective: To compare fees for biopsy, treatment procedure, repair, and 2-month follow-up for nonmelanoma skin cancer (NMSC) treatments: electrodesiccation and curettage (ED&C), excision, and Mohs micrographic surgery (MMS).

Methods: A cost comparison of 936 primary NMSCs diagnosed in 1999/2000 at a University affiliated dermatology practice. Clinical data was from medical record review.

Economic analysis of cinacalcet in combination with low-dose vitamin D versus flexible-dose vitamin D in treating secondary hyperparathyroidism in hemodialysis patients.

Background: The ACHIEVE (Optimizing the Treatment of Secondary Hyperparathyroidism: A Comparison of Sensipar and Low Dose Vitamin D vs Escalating Doses of Vitamin D Alone) trial evaluated the efficacy of treatment with cinacalcet plus low-dose activated vitamin D analogues (Cinacalcet-D) compared with vitamin D analogues alone (Flex-D) in attaining KDOQI (Kidney Disease Outcomes Quality Initiative) targets for secondary hyperparathyroidism (SHPT). The economic implications of these treatment regimens have not been explored.

Study Design: Economic analysis of SHPT treatment in hemodialysis patients.

Current trends in Graz Brain-Computer Interface (BCI) research.

This paper describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns. EEG signals recorded from sensorimotor areas during mental imagination of specific movements are classified on-line and used e.g.

Frequency component selection for an EEG-based brain to computer interface.

A new communication channel for severely handicapped people could be opened with a direct brain to computer interface (BCI). Such a system classifies electrical brain signals online. In a series of training sessions, where electroencephalograph (EEG) signals are recorded on the intact scalp, a classifier is trained to discriminate a limited number of different brain states.

Feature extraction for on-line EEG classification using principal components and linear discriminants.

The study focuses on the problems of dimensionality reduction by means of principal component analysis (PCA) in the context of single-trial EEG data classification (i.e. discriminating between imagined left- and right-hand movement).

EEG-based discrimination between imagination of right and left hand movement.

Three subjects were asked to imagine either right or left hand movement depending on a visual cue stimulus. The interval between two consecutive imagination tasks was > 10 s. Each subject imagined a total of 160 hand movements in each of 3-4 sessions (training) without feedback and 7-8 sessions with feedback.

On-line EEG classification during externally-paced hand movements using a neural network-based classifier.

EEGs of 6 normal subjects were recorded during sequences of periodic left or right hand movement. Left or right was indicated by a visual cue. The question posed was: 'Is it possible to move a cursor on a monitor to the right or left side using the EEG signals for cursor control?' For this purpose the EEG during performance of hand movement was analyzed and classified on-line.

EEG-based brain computer interface (BCI). Search for optimal electrode positions and frequency components.

Several laboratories around the world have recently started to investigate EEG-based brain computer interface (BCI) systems in order to create a new communication channel for subjects with severe motor impairments. The present paper describes an initial evaluation of 64-channel EEG data recorded while subjects used one EEG channel over the left sensorimotor area to control on-line vertical cursor movement. Targets were given at the top or bottom of a computer screen.

Visualization of sensorimotor areas involved in preparation for hand movement based on classification of mu and central beta rhythms in single EEG trials in man.

It is well known that mu and central beta rhythms start to desynchronize > 1 s before active hand or finger movement. To investigate whether the same cortical areas are involved in desynchronization of mu and central beta rhythms, 56-channel EEG recordings were made during right- and left-finger flexions in three normal subjects. The event-related desynchronization (ERD) was quantified in single EEG trials and classified by the Distinction Sensitive Learning Vector Quantization (DSLVQ) algorithm.

Selection of electrode positions for an EEG-based brain computer interface (BCI).

One major question in designing an EEG-based Brain Computer Interface to bypass the normal motor pathways is the selection of proper electrode positions. This study investigates electrode selection with a Distinction Sensitive Learning Vector Quantizer (DSLVQ). DSLVQ is an extended Learning Vector Quantizer (LVQ) which employs a weighted distance function for dynamical scaling and feature selection.