Hemaapp Anemia Apk Download

The mobile app is not intended to replace blood tests, which remain the most accurate way to measure hemoglobin. But the early test results, from patients that ranged in age from 6 to 77 years old, suggest HemaApp can be an effective and affordable initial screening tool to determine whether further blood testing is warranted. When used to screen for anemia, HemaApp correctly identified cases of low hemoglobin levels 79 percent of the time using just the phone camera, and 86 percent of the time when aided with some light sources.

A team of researchers from the University of Washington have developed an app that turns smartphones into anemia detectors. See, the condition often goes undiagnosed in developing parts of the world. And seeing as it's the most common blood disorder out there, it likely affects more than 25 percent of the population that the World Health Organization believes it does. HemaApp gives medical professionals a way to see if patients have anemia simply by shining the phone's flash against their skin.

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The app estimates hemoglobin concentrations -- anemia is characterized by low levels of hemoglobin or red blood cells -- by analyzing the color of a person's blood. UW's researchers found that it was most accurate when used with a low-cost LED lighting attachment on top of the flash, allowing it to see more of what's under the patient's skin. In fact, it was as accurate as the Masimo Pronto, the expensive FDA-approved machine that can measure hemoglobin non-invasively using a device clipped to a person's finger. A smartphone loaded with the HemaApp will be much cheaper and accessible for medical professionals in developing nations.

This team of researchers built on the work by another U of Washington group that developed an app that can detect jaundice in babies. They plan to improve their technology further to be able to screen for sickle cell disease and other blood disorders. Despite what it can do, HemaApp will mostly be used for initial screening, and people who exhibit low hemoglobin levels still have to get a blood test. It will at least allow doctors and nurses to pluck those who need further tests from a bigger number of people, though, so they won't have to take blood samples for anemia if they don't have to.

Iron deficiency in human blood not only indicates anemia but can also signify malnutrition. Researchers and health workers in the field, particularly those focused on detecting malnutrition in children in developing countries, need fast, inexpensive, safe, and accurate hemoglobin level tests.

In addition to providing a field tool useful in detecting childhood malnutrition, HemaApp could also be useful for patients with anemia who want to track their iron levels. HemaApp has personal significance for me, as I have an ongoing issue with blood iron and would love the ability to quickly and accurately test my iron level at home.

We introduce a paradigm of completely non-invasive, on-demand diagnostics that may replace common blood-based laboratory tests using only a smartphone app and photos. We initially targeted anemia, a blood condition characterized by low blood hemoglobin levels that afflicts >2 billion people. Our app estimates hemoglobin levels by analyzing color and metadata of fingernail bed smartphone photos and detects anemia (hemoglobin levels

Due to its high prevalence affecting over 2 billion people globally, anemia, characterized by low blood hemoglobin (Hgb) levels6, was chosen as the initial disease target for us to study. Anemia has numerous causes, ranging from common nutritional causes, such as iron or folate deficiency, which are relatively straightforward to treat and cure, to rarer genetic causes, such as sickle cell disease or thalassemia major, which lead to severe and chronic anemia that requires frequent monitoring. Detection of anemia involves either anemia screening or anemia diagnosis, and both require different degrees of measurement accuracy. First, a clear clinical need exists for easily and widely accessible tools to screen for anemia among at-risk populations (e.g., pregnant women, toddler-age children, elderly patients) or the general public to determine whether an individual will need formal confirmatory testing with the gold standard Hgb level test obtained via a complete blood count (CBC). However, there is also a need to for non-invasive methods to more quantitatively and officially diagnose and monitor anemia with higher precision Hgb levels, especially patients with known or chronic anemia.

Given the performance of this technology and high prevalence of anemia worldwide, afflicting nearly two billion people, especially young children, the elderly, and pregnant women, worldwide, this completely noninvasive technology that requires only photos obtained from smartphones has significant implications as a widely accessible screening tool for at risk populations and the general population. The ability to inexpensively diagnose anemia with a high sensitivity, completely noninvasively and without the need for any external smartphone attachments or calibration equipment represents a significant improvement over current POC anemia screening. The external equipment requirements of current existing POC anemia screening technologies represent a significant hurdle for use, as each additional piece of equipment requires a supply chain to support it. For example, even relatively low-cost color calibration cards used to normalize for different background lighting require distribution to the patient and quality control measures regarding the manufacturing process to ensure that the colors are printed precisely and accurately on each card.

Optimizing sensitivity is of paramount importance for a screening tool, due to the ability to correctly identify a high percentage of anemia cases even if this negatively impacts specificity. In its current form, our technology requires the user to simply obtain a fingernail image, which can then be analyzed with an on-board smartphone app that comprises our image analysis algorithm to output the Hgb level measurement or be transmitted remotely to another device (e.g., laptop, desktop computer, cloud-based server with our algorithm embedded into their systems) for remote analysis, the results of which can be immediately transmitted back to the user. After identifying subjects that may possibly be anemic, either type of system can recommend confirmatory Hgb level testing with a CBC, allowing any false positives to avoid unnecessary treatment. Given the ever-increasing rate and near ubiquity of smartphone ownership worldwide36, this noninvasive, inexpensive, patient-operated Hgb measurement algorithm allows those at risk of anemia to monitor their conditions using only the native hardware included with their own smartphone2,3. This is particularly pertinent in low resource settings, where, contradictory to the relative lack of medical infrastructure, mobile phone networks are quite extensive and have leapfrogged landlines37.

Additionally, this system has the potential to fundamentally alter the management of patients with chronic anemia. During the course of several weeks, a patient may take images of their fingernail beds and enter their CBC-measured Hgb levels that were obtained as part of their regular outpatient clinical care. Results suggest that these images and Hgb levels may be used to teach the smartphone phone to develop a calibration personalized and tailored to each individual patient. In times of clinical stress, these patients, such as those with genetic causes of anemia or cancer undergoing chemotherapy, may experience rapid, life-threatening, precipitous drops in Hgb and require constant monitoring to determine their need for transfusions. Using this technology, patients could potentially self-monitor their anemia from the comfort of their own home, rather than through inconvenient and recurring clinic visits. In addition, some patients with chronic anemia due to a genetic etiology require chronic transfusions to survive. These scheduled transfusions are currently administered at convenient and regular intervals, and not based on clinical need38. Hence, a patient may be transfused too early, exposing them to unnecessary transfusion-related effects (i.e., iron overload, risk of infection), while patients transfused too late may require urgent hospitalization if they develop symptomatic anemia or their Hgb levels decrease to a dangerous level. By enabling continuous and simple monitoring, this technique may empower patients and lead to better allocation of blood bank resources. Moreover, further data collection will increase the size of the patient image pool, facilitating the incorporation of deep machine learning Big Data techniques to further refine the Hgb measurement algorithm39.

This system suffers from the potential to be impacted by diseases which cause nailbed discolorations such as jaundice and cyanosis42,43. However, it is important to point out that a large population of our study subjects suffered from hemolytic anemias, which can lead to jaundice. We found no correlation between disease state and Hgb measurement error, indicating that jaundice is unlikely to impact Hgb measurement (Fig. 4). Furthermore, the image analysis algorithm can potentially be trained in future studies on populations with these disorders to take these discolorations into account. We would also argue that suffering from cardiovascular dysfunction sufficient to cause cyanosis, is a significant enough health problem to render anemia diagnosis a secondary concern, thus obviating the need for these patients to use this app under those circumstances. While these conditions may present challenges in Hgb measurement, they present a promising opportunity to use the app to screen for such diseases.

The primary limitations in this study were derived from the use of a single smartphone model and test administrator. Going forward, the potential for user error as well as inter/intra-smartphone variability leading to Hgb measurement error will be addressed in the form of a full clinical assessment, and we will also investigate the efficacy of the smartphone image-based algorithm in which patients will use this app as a self-test using multiple models and manufacturers of smartphones. This study will also evaluate and improve upon our quality control measures. Overall, the ability to conduct rapid on-demand self-testing demonstrates the versatility of the system and could be especially conducive for global heath applications, where remote diagnosis coupled with tight quality control measures may be preferred and enabled by increasing smartphone use and mobile network prevalence in low resource settings36. This approach will shift the anemia screening paradigm worldwide by empowering patients to test themselves from the comfort of their own homes, wherever and whenever they desire. ff782bc1db