Currently there is no early dehydration detection system using temperature and pH as indicators. A sensor could alert the wearer and others of low hydration levels, which would normally be difficult to catch prior to more serious complications resulting from dehydration. In this study, a protein fluorophore, green fluorescent protein (GFP), and a chemical fluorophore, fluorescein, were tested for a change in fluorescence in response to increased temperature or decreased pH. Reversing the pH change did not restore GFP fluorescence, but that of fluorescein was re-established. This finding suggests that fluorescein could be used as a reusable sensor for a dehydration-related pH change.
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Uncovering the hidden trafficking trade with geographic data and natural language processing
The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.
Read More...A novel deep learning model for visibility correction of environmental factors in autonomous vehicles
Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.
Read More...Predictions of neural control deficits in elders with subjective memory complaints and Alzheimer’s disease
The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...Transfer Learning with Convolutional Neural Network-Based Models for Skin Cancer Classification
Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.
Read More...A machine learning approach to detect renal calculi by studying the physical characteristics of urine
The authors trained a machine learning model to detect kidney stones based on characteristics of urine. This method would allow for detection of kidney stones prior to the onset of noticeable symptoms by the patient.
Read More...Utilizing a novel T1rho method to detect spinal degeneration via magnetic resonance imaging
Spinal degeneration has been linked to critical conditions such as osteoarthritis in adults aged 40+; while this condition is considered to be irreversible, we took interest in magnetic resonance imaging (MRI) for early detection of the condition. Ultimately, our purpose was to determine the effectiveness of a relatively novel T1rho method in the early detection of spinal degeneration, and we hypothesized that the early to mild progression of spinal degeneration would affect T1rho values following an MRI scan.
Read More...The Development of a Highly Sensitive Home Diagnosis Kit for Group A Streptococcus Bacteria (GAS)
In this article, Mai et al. have developed a do-it-yourself kit for the detection of Strep A bacterial infections. While Strep A infections require antibiotic administration, viral infections, which can present with similar symptoms, often resolve on their own. The problem with delayed antibiotic treatment is an increasing risk of complications. Currently an accurate diagnosis requires that patients make the trip to the hospital where sensitive tests can be performed. The method described here, bundled into a commercially available kit, could help speed up the identification of such bacterial infections. When presented with symptoms of a sore throat and fever, you could just buy the kit at your local pharmacy, perform the simple yet highly accurate and sensitive test, and know whether an urgent trip to the doctor's for an antibiotic prescription is necessary. How convenient!
Read More...Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease
Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases worldwide, but there are few studied warning signs for early detection of the disease. Here, researchers study alterations that occur in a mouse model of NAFLD, which indicate the onset of NAFLD sooner. Earlier detection of diseases can lead to better prevention and treatment.
Read More...Creating a drought prediction model using convolutional neural networks
Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.
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