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Aid suspended in Northern Nigeria by UN after the attack on Convoy

The U.N. children's agency, UNICEF, says an employee and a contractor were injured in the attack and are being treated at a local hospital.

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UNICEF suspended aid in Borno district. Image Source: www.vanguardngr.com
  • The U.N. children’s agency, UNICEF, says an employee and a contractor were injured in the attack and are being treated at a local hospital
  • The convoy was in Borno state, carrying humanitarian aid from the town of Bama to Maiduguri, in the heart of the area where the militant group Boko Haram operates
  • The charity Doctors Without Borders warned this week that more than 500,000 people in Borno state urgently need emergency assistance

The United Nations says it is suspending humanitarian assistance missions to Nigeria’s Borno state pending a security review, after an aid convoy was ambushed by unidentified attackers Thursday in northern Nigeria.

UNICEF suspended aid in Borno district. Image Source: www.un.org
UNICEF suspended aid in Borno district. Image Source: www.un.org

The U.N. children’s agency, UNICEF, says an employee and a contractor were injured in the attack and are being treated at a local hospital. It did not elaborate.

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The convoy was in Borno state, carrying humanitarian aid from the town of Bama to Maiduguri, in the heart of the area where the militant group Boko Haram operates. In a statement, UNICEF says the assistance was “desperately needed.”

“This was not only an attack on humanitarian workers. It is an attack on people who most need the assistance and aid that these workers were bringing,” the statement continued.

Boko Haram. Image Source: www.abc.net.au
Boko Haram. Image Source: www.abc.net.au

The charity Doctors Without Borders warned this week that more than 500,000 people in Borno state urgently need emergency assistance.

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It said 15,000 people in the town of Banki have been isolated by Boko Haram violence and depend entirely on humanitarian aid. A Doctors Without Borders representative said most Banki residents have been in hiding for more than a year because of Boko Haram violence.

Months of food shortages have resulted in a catastrophic health situation, with very high levels of malnutrition, particularly among small children.

Source: VoaNews

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Machine Learning Can Help Doctors to Improve End-Of-Life Conversation with Patients

A deeper understanding of these conversations, which are often freighted with emotion and uncertainty, will also help reveal what aspects or behaviors associated with these conversations are more valuable for patients and families

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Machine Learning
A Research used Machine Learning algorithms to analyze 354 transcripts of palliative care conversations collected by the Palliative Care Communication Research Initiative, involving 231 patients. Pixabay

Researchers at University of Vermont have used Machine Learning and natural language processing (NLP) to better understand conversations about death, which could eventually help doctors improve their end-of-life communication.

Some of the most important, and difficult, conversations in healthcare are the ones that happen amid serious and life-threatening illnesses.

Discussions of the treatment options and prognoses in these settings are a delicate balance for doctors and nurses who are dealing with people at their most vulnerable point and may not fully understand what the future holds.

“We want to understand this complex thing called a conversation. Our major goal is to scale up the measurement of conversations so we can re-engineer the healthcare system to communicate better,” said Robert Gramling, director of the Vermont Conversation Lab in the study published in the journal Patient Education and Counselling.

Gramling and his colleagues used machine learning algorithms to analyze 354 transcripts of palliative care conversations collected by the Palliative Care Communication Research Initiative, involving 231 patients.

They broke each conversation into 10 parts with an equal number of words in each, and examined how the frequency and distribution of words referring to time, illness terminology, sentiment and words indicating possibility and desirability changed between each decile.

“We picked up some strong signals,” said Gramling.

Conversations tended to progress from talking about the past to talking about the future, and from sadder to happier sentiments. “There was quite a range, they went from pretty sad to pretty happy,” Gramling added.

Machine Learning
Researchers at University of Vermont have used Machine Learning and natural language processing (NLP) to better understand conversations about death, which could eventually help doctors improve their end-of-life communication. Pixabay

The consistent results across multiple conversations show just how much people make meaning out of stories in healthcare.

“What we found supports the importance of narrative in medicine,” he said.

That knowledge could eventually help healthcare practitioners understand what makes a “good” conversation about palliative care, and how different kinds of conversations might require different responses.
That could help create interventions that are matched to what the conversation indicates the patient needs the most.

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A deeper understanding of these conversations, which are often freighted with emotion and uncertainty, will also help reveal what aspects or behaviors associated with these conversations are more valuable for patients and families. (IANS)