Ten 'one-stop shop' cancer diagnosis centres planned for England

New Scientist

Ten centres offering a one-stop shop for spotting cancer are to be set up in England. The aim is to provide rapid testing for multiple cancers, cutting the often lengthy wait for diagnosis. The UK currently lags behind other western European countries and nations such as Australia and Canada in terms of cancer survival. This is at least partly due to delays in diagnosis and treatment. Around half of people with cancer have vague or non-specific symptoms, such as loss of appetite or weight.

Endometriosis diagnosis: 'A relief to know I wasn't mad'

BBC News

Alex Roach was 20 when she was told she had endometriosis, seven years after first suffering severe pain when her periods began. The Cardiff-based lawyer has had three lots of surgery because of the condition, which causes the womb lining to grow in other parts of the body and can lead to crippling pain, fatigue and infertility. As the disease cannot be cured, she may need further surgery and her ability to conceive could be affected. She has backed the findings of a Welsh Government investigatory report which calls for improved understanding of the condition in medical staff, earlier diagnosis and treatment, better education and more specialist help. She said of her eventual diagnosis: "It was quite bittersweet. It was a relief to know I wasn't mad."

AI Diagnosis Tool Bridges The Gap Between Doctors And Patients


VisualDx aims to tackle the problems in the healthcare sector on both fronts, by reducing the workload of doctors both inside and outside the hospital. The tool aims to assist primary physicians by identifying rare diseases or unusual variations of common diseases as early as possible, by analyzing images of skin-presenting symptoms. 'Diagnosis is a process of inching ourselves to a more secure position, it's very different from knowing answers,' says CEO Art Papier. But given that'the hardest area for primary care workers is skin-presenting diseases,' allowing first-contact doctors to identify diseases during the early stages of treatment could lead to more accurate diagnoses, minimize referrals to specialists, and save time and money further down the line.

Characterizing Diagnoses

AAAI Conferences

The diagnostic task is to determine why a correctly designed system is not functioning as it was intended - the explanation for the faulty behavior being that the particular system under consideration is at variance in some way with its design. One of the main subtasks of diagnosis is to determine what could be wrong with a system given the observations that have been made. Most approaches to model-based diagnosis [4] characterize all the diagnoses for a system as the minimal sets of failing components which explain the symptoms. Although this method of characterizing diagnoses is adequate for diagnostic approaches which model only the correct behavior of components, it does not generalize. For example, it does not necessarily extend to approaches which incorporate models of faulty behavior [24] or which incorporate strategies for exonerating components [19].

Exploring the Duality in Conflict-Directed Model-Based Diagnosis

AAAI Conferences

A model-based diagnosis problem occurs when an observation is inconsistent with the assumption that the diagnosed system is not faulty. The task of a diagnosis engine is to compute diagnoses, which are assumptions on the health of components in the diagnosed system that explain the observation. In this paper, we extend Reiter's well-known theory of diagnosis by exploiting the duality of the relation between conflicts and diagnoses. This duality means that a diagnosis is a hitting set of conflicts, but a conflict is also a hitting set of diagnoses. We use this property to interleave the search for diagnoses and conflicts: a set of conflicts can guide the search for diagnosis, and the computed diagnoses can guide the search for more conflicts. We provide the formal basis for this dual conflict-diagnosis relation, and propose a novel diagnosis algorithm that exploits this duality. Experimental results show that the new algorithm is able to find a minimal cardinality diagnosis faster than the well-known Conflict-Directed A*.