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Third Workshop on Data Mining for Healthcare Management

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, la prevención y detección de fraude médico , detección de fallos de los dispositivos médicos , las estrategias de salud para mejorar la calidad , la privacidad y la eficiencia. Data mining techniques are helping in various aspects of health management, including disease diagnosis, decision making for treatment, prevention and detection of medical fraud, fault detection of medical devices, strategies health to improve the quality, privacy and efficiency.

DMHM ) es un campo emergente , donde investigadores académicos y la industria han reconocido el potencial de su impacto para mejorar la asistencia sanitaria, mediante el descubrimiento de patrones y tendencias a partir de grandes volúmenes de datos complejos, generados por las transacciones de atención médica. The Data Mining for Health Management (DMHM) is an emerging field where academic researchers and industry have recognized the potential impact to improve health care through the discovery of patterns and trends from large volumes of complex data generated for health care transactions.

Data mining also helps to discover new business ideas or making decisions that may affect cost efficiency while maintaining high quality of care.
The conference will be held on 29/Mayo - 31/Junio ​​in Kuala Lumpur: http://pakdd2012.pakdd.org/

ISSUES EXPECTED

·   Improving Quality of products and services

·   Data collection and integration Techniques

·   Data cleaning and transformation

·   Knowledge models based medical recommendation

·   Information visualization of medical data.

·   Enhancing quality of tools available to healthcare providers.

·   Medical device fault detection and prevention.

·   Reliability of medical devices.

·   Pattern recognition in medical images and data.

·   Improving Quality of products and services

·   Data collection and integration Techniques

·   Data cleaning and transformation

·   Knowledge models based medical recommendation

·   Information visualization of medical data.

·   Enhancing quality of tools available to healthcare providers

·   Medical device fault detection and prevention

·   Reliability of medical devices

·   Pattern recognition in medical images and data

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