5 research outputs found

    Using machine learning to provide automatic image annotation for wildlife camera traps in the Arctic

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    Source at https://hdl.handle.net/10037/26504.The arctic tundra is considered the terrestrial biome expected to be most impacted by climate change, with temperatures projected to increase as much as 10 °C by the turn of the century. The Climate-ecological Observatory for Arctic Tundra (COAT) project monitors the climate and ecosystems using several sensor types. We report on results from projects that automate image annotations from two of the camera traps used by COAT: an artificial tunnel under the snow for capturing information about small mammals, and an open-air camera trap using bait that captures information of a range of larger sized birds and mammals. These traps currently produce over two million pictures per year. We have developed and trained several Convolutional Neural Network (CNN) models to automate annotation of images from these camera traps. Results show that we get a high accuracy: 97.84% for tunnel traps, and 94.1% for bait traps. This exceeds previous state of the art in animal identification on camera trap images, and is at a level where we can already relieve experts from manual annotation of images

    Bedside Ultrasound for the Diagnosis of Small Bowel Obstruction

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    History of present illness: An elderly female with no history of prior abdominal surgeries presented to the emergency department (ED) with acute onset of abdominal pain and distention. Upon arrival, she began having large volume bilious emesis. While waiting for a computed tomography (CT) scan of her abdomen and pelvis, a point of care ultrasound (POCUS) was performed which showed evidence of a small bowel obstruction (SBO). The patient had a nasogastric tube placed that put out over two liters of bilious contents. A subsequent CT scan confirmed the diagnosis of SBO from a left inguinal hernia and the patient was admitted to the surgical service. Significant findings: The POCUS utilizing the low frequency curvilinear probe demonstrates fluid-filled, dilated bowel loops greater than 2.5cm with to-and-fro peristalsis, and thickened bowel walls greater than 3mm, concerning for SBO. Discussion: Gastrointestinal obstruction is a common diagnosis in the ED, accounting for approximately 15% of all ED visits for acute abdominal pain.1 SBO accounts for approximately 80% of all obstructions.2 In the diagnosis of SBO, studies show that abdominal x-rays have a sensitivity of 66-77% and specificity of 50-57%,3 CT scans have a sensitivity of 92% and specificity of 93%,4 and ultrasound has a sensitivity of 88% and specificity of 96%.5 While CT scan remains a widely accepted modality for diagnosing SBO, ultrasound is more cost effective, well tolerated, does not involve ionizing radiation, and can be done in a timely manner at the patient’s bedside. Ultrasound can also identify transition points as well as distinguish between functional and mechanical obstruction.6 In addition to SBO, ultrasound can be used to diagnose external hernias, intussusception, tumors, superior mesenteric artery (SMA) syndrome, foreign bodies, bezoars, and ascariasis.

    Interposed Abdominal Compression CPR for an Out-of-Hospital Cardiac Arrest Victim Failing Traditional CPR

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    Interposed abdominal compression CPR is an alternative technique to traditional CPR that can improve perfusion and lead to restoration of circulation in patients with chest wall deformity either acquired through vigorous CPR or co-morbidity such as COPD.  We report a case of out-of-hospital cardiac arrest where IAC-CPR allowed for restoration of spontaneous circulation and eventual full neurologic recovery when traditional CPR was failing to generate adequate pulses with chest compression alone
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