HELPING NATURE: FEED A BEE

Here it was, a bumble bee tired and in search for something sweet. It landed near the deck and when trying to get in the air again it came down again. This is where mothers come in and know what is required: some jam to get the energy levels back up. It made for some very nice pictures.

DATA-MINING AS A TOOL TO PREDICT DOMESTIC VIOLENCE

Domestic violence being a serious problem in New Zealand. In 2006 police recorded 71,000 family violence related incidents. One in four women and just under one in five men would be the victim of domestic violence at some stage in their lifetime, according to an article identified at Stuff.co.nz dated 21 December 2008. Newly released crime statistics show a 13 percent jump in the number of domestic violence incidents that have been reported to police in the last year. There was growth in every area of family violence, including murder. Information exclusively obtained by 3 News also shows more women are seeking financial assistance to escape (Source: 3 News 1 October 2009). A number of the victims will end up with their GP or in an emergency room, yet overall the diagnosis of domestic abuse is often not diagnosed and a it is estimated that two thirds assualts go unreported. Would it not be a great thing if the risk of domestic abuse could be predicted on the basis of available data so as to enable the right parties to start asking questions instead of waiting for a report? Wouldn’t that potentially prevent a lot of harm? Well, a group of researchers at Harvard University created the first computer model to detect the risk of abuse at home.

It is a known fact that domestic abuse often goes unnoticed at doctors’ visits and patients often even try to hide abuse. Ben Reis, Harvard pediatrician and computer scientist as well as the designer of the new model, tigether with his colleagues, tapped into a public U.S. database containing six years of medical history for around half a million people. The data was fed into a predictive computer model that subsequently calculated the abuse risks linked to different diagnoses such as burns, sprains or mental disorders.

The advantage of such an approach is that physicians would no longer have to trawl through extensive medical records in what limited time they have, instead they would be presented with a single graphic: the so called “risk gel.” The graph shows the patients medical history as a collection of colored bars, with green bars meaning no risk an red bars meaning a risk that the diagnosis is statistically linked to abuse. The computer subsequently calculates the combined abuse risk.

When determined as high the physician is alarmed about that and made aware that a face-to-face meeting with the patient may be called for. The system is meant as a screening system. Using the system the researchers were able to make a diagnosis of abuse two years prior to that diagnosis by physician and the system was able to pick up signs not revealed by the patient yet. Less than 20% of the patients ffalgged as high risk cases by the system turned out to have actually been diagnosed with abuse. The researchers pointed out that data is far from up to speed when it comes to diagnosing abuse and prediuct that the task will get easier as electronic medical records are becoming more common. Previous trials with screening have shown that the screening is not the end-all and that adequate training is required in approaching patients/victims with the suspicions. The researchers hope to have a full fledged system ready, including user interface, in for years.

The full article including links to more information is available at Wired Science

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