How Advanced Pollen App Forecasts Can Maintain Quality in an eHealth Service (1)

1
How Advanced Can Pollen App Forecasts Maintain
Quality in an eHealth service?
2
Introduction

• Allergies to pollen are a major global health
  issue. They have a sizable impact on a sizeable
  portion of the population in many nations. Pollen
  forecast have proven to be a very useful tool for
  managing and treating allergies to pollen. People
  consume pollen information more frequently during
  the season, indicating that such services are
  necessary. The public is now informed about
  pollen forecasts via mobile technology (phones,
  tablets, and other wireless devices), so mobile
  health (mHealth) is becoming more significant. To
  prevent unexpected outcomes, norms and an ethical
  framework still need to be developed for
  eHealth.  Additionally, the World Health
  Organization conducted a global survey on
  eHealth, which revealed a rise in eHealth and
  mHealth activity in nations with higher incomes.

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mHealth

• The treatment of asthma and allergy disorders may
  be improved through web applications (apps),
  wearables, and other personal monitoring tools.
  The capacity to longitudinally gather data on
  symptoms inhaler usage is one of the benefits
  of asthma applications that have been suggested
  since it enables the identification of shifts
  over time to assist patients and caregivers in
  determining if the symptoms are getting worse. It
  is possible to incorporate information from
  outside sources, such as weather, allergy load,
  and air quality reports. The allergy clinicians
  can receive the data gathered by the apps either
  in-person or through telemedicine portals.

4
Digital health records

• Large amounts of actual data are produced due to
  the widespread adoption of electronic health
  records in the healthcare industry. The
  artificial intelligence (AI) method called
  natural language processing uses clinical
  narratives from electronic health records to
  extract information.  Electronic health records
  can enable temporal condition pattern mining,
  which may reveal undetected relationships between
  illnesses and guide future causality studies. The
  use of these technologies in allergy treatment is
  still in its early phases of development. Studies
  have used electronic health data to estimate the
  frequency of drug or food allergies in various
  populations. Analyzing this information, a
  natural language recognition algorithm has been
  proven to identify asthma. AI may someday be used
  to identify allergy patients and treat them
  before their conditions worsen. This may be
  especially pertinent to patients who missed
  consultations or had to stop receiving therapy
  because of the COVID-19 outbreak.

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Recommendations And Potential Future Routes

• To support people with pollen forecasts
  allergies, mobile apps that deal with allergen
  avoidance must meet several requirements and
  functionalities, including easy-to-understand
  pollen forecasts, at least a few forecasted
  aeroallergens, herbal information, symptom
  diaries, allergic rhinitis risk questionnaires,
  and an imprint from the app's publisher
  identifying the institution that is, ideally,
  free from conflicts of interest. It is to be
  noted that pollen information applications
  frequently contain advertisements, particularly
  if the publisher is a business and not a company
  involved directly in pollen forecasting. The
  applications "Biowetter," "Pollenflug," and
  "Hayfever" all contain direct advertisements.
  Information that is vital to know is represented
  by the apps publisher. In terms of incidence in
  the imprint, a forecasting institution appears in
  the backdrop of the applications "Pollen," "DWD,"
  and "Pollen News," but not in the other six apps.
  The findings of this study highlight the need for
  pollen forecasts to be improved and held to
  higher standards.

6
Ambee pollen app

• More than 50 million Americans have various sorts
  of allergies each year, making them the sixth
  most common chronic ailment, according to the
  AAFA (Asthma allergy foundation of America). As
  per survey, pollen negatively impacts people's
  health by causing various seasonal allergies,
  including respiratory conditions. "The issue is
  that accurate results must be gathered using a
  complicated process. Currently, most pollen
  forecasts give a fairly broad estimate, and part
  of the issue is that there aren't enough stations
  for pollen counting."
• Ambee's pollen app uses machine learning-based AI
  algorithms to track pollen. To ensure accuracy,
  it combines pollen data from several sources with
  on-ground sensors, satellite imaging, and
  statistical inference. We are Asia's only
  pollen-tracking API to give real-time pollen data
  sets across the world.
• Healthcare, pharmaceutical, and weather companies
  use Ambee's pollen data. When marketing its
  anti-allergy product, Kleenex, a company that
  sells paper-based items, had a 200 boost in
  website traffic.
• Ambee's pollen app swiftly and easily delivers
  real-time data for a seamless user experience. It
  is simple to incorporate into any program, app,
  or product and is user-friendly for developers.
• The pollen dataset offers pollen counts and
  danger levels for many categories. It provides
  overall risk alerts for over 90 different pollen
  species. The dataset provides information on
  different types of pollen, grass, weeds, and
  trees.