Women’s Biggest Healthcare Weapon? Artificial Intelligence

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Women’s health is a pressing issue around the world. Globally, women face significant disparities in healthcare access and outcomes. Socioeconomic factors, cultural barriers, and systemic biases contribute to this inequality.

When women’s health is considered, it is often reduced to reproductive health, but gender biases in medical research and healthcare delivery can affect the way women are diagnosed and treated for a range of health conditions, such as heart disease.

Research shows that 43% of women’s health burdens stem from conditions that do not affect women disproportionately or differently than men.

Addressing the women’s health gap could boost the global economy by $1 trillion every year by 2040, according to McKinsey. Technology is key to this, changing how we address women’s health needs and improving health outcomes.

Key Takeaways

  • Globally, women face significant disparities in healthcare access and outcomes due to socioeconomic, cultural, and systemic biases.
  • AI and technology can bridge the gender health gap by improving outcomes, enhancing preventive care, and promoting informed decision-making.
  • AI-powered imaging and telemedicine platforms offer early detection and remote access, overcoming geographical and financial barriers.
  • Federated AI and blockchain can ensure data privacy and decentralize data analysis, enhancing trust and security in women’s healthcare.
  • Addressing women’s health gaps could significantly boost the global economy, but integrating technology requires overcoming several challenges.

The Ways Tech Can Bridge the Gender Health Gap

The historical lack of research into women’s health — it has only been 30 years since women were broadly included in clinical trials — means there is a lack of data for developing new drugs and treatments. Just 1% of healthcare research and innovation is invested in conditions beyond oncology that affect women specifically.


Artificial intelligence (AI) offers opportunities to improve outcomes, enhance preventive care, and promote empowerment through informed decision-making. It can quickly collect and analyze vast repositories of data for researchers, including genetic information, medical records, and lifestyle factors. It can also help healthcare professionals to provide personalized care based on this data, leading to more effective interventions.

One of the critical aspects of women’s healthcare is the importance of early detection of conditions like breast cancer and cervical cancer. AI-powered imaging technologies, such as mammography and Pap smear analysis, can help healthcare providers to identify abnormalities in their early stages so that they can intervene faster and improve survival rates.

Monica Cepak, CEO of Wisp, called AI “one of the most transformational developments in healthcare” at the CES conference in Las Vegas earlier this year.

I would caution against losing that human touchit is so important—but when you think about being able to deliver personalized care at scale, AI is the future.”

Rebekah Gee, Founder and CEO at Nest Health, added: “There’s so many insights driven by data that are not being taken advantage of and are leading to poor outcomes, and so this kind of revolution and value-based care… is becoming more and more common.”

“Data is becoming democratized. There’s much more interest in funding companies like Nest and considering policy solutions that utilize data.

“I’m very optimistic that we’re going to finally catch up in healthcare and think about predictive modeling and how we can actually understand health.”

AI-driven virtual assistants and telemedicine platforms can offer convenient ways for women to access healthcare services remotely.

These platforms can provide accurate health information, offer assessments of symptoms, and facilitate virtual consultations with healthcare professionals. This is key to overcoming common barriers to access, such as geographical distance, time constraints, and financial constraints.

AI can work with wearable devices such as smart watches, fitness trackers, heart and blood pressure monitors, and biosensors to continuously monitor data from individuals.

By calculating personal baselines for resting heart rate, resting respiratory, and so on, AI algorithms and machine learning can detect patterns and determine when there is a statistically significant change. Medical professionals can then intervene faster and provide care that is appropriate and tailored to the individual, rather than treatment based on research that is less relevant to women.

Combined with telehealth applications, this is a game changer for managing women’s health through virtual consultations and remote monitoring in rural and underserved communities.

“Telehealth is just one piece of a much larger care ecosystem. The future of hybrid health is really what’s most exciting,” Cepak said.

“Being able to combine diagnostics with in-person care as well as telehealth and bringing all of those elements together under one roof and building a seamless patient experience… It’s not enough to just provide a prescription, it’s about those ongoing more personalized services that really drive the most value for patients.”

“The ways that we’re integrating in-person and digital are really exciting, Gee added.

“Remote patient monitoring codes have been one incentive, one tailwind for being able to create a payment model around monitoring patients who are vulnerable at home and reaching those patients,” said Carolyn Walsh, Chief Commercial Officer at BioIntelliSense.

“It’s about being able to reach and create an extension out into the community where the technology can become much more ubiquitous and pervasive.”

The Importance of Federated Systems

One of the challenges of integrating AI into healthcare is patient confidentiality and data privacy.

Federated AI, which trains models on multiple distributed datasets, is a decentralized approach that can combine data from around the world without transferring it to a centralized location or revealing individuals’ personal information.

Nvidia, which is leading in supplying the hardware and software platforms for AI systems, has developed the Clara AI Toolkit for healthcare.

Organizations like Massachusetts General Hospital (MGH), in collaboration with Brigham and Women’s Hospital’s (BWH) Center for Clinical Data Science (CCDS), are using the toolkit to develop AI models through federated learning.

The CCDS started using Clara in 2019 to improve a pre-trained AI model developed at Partners HealthCare by accumulating individual contributions from diverse datasets.

“Federated learning enables collaborative, decentralized training of AI models without the need to share patient data,” said Ittai Dayan, MD, Executive Director at CCDS, at the time.

“Aggregating knowledge from various institutions creates a more robust, accurate and generalizable AI product. This approach has the potential to improve ‘model resiliency’ and reduce bias.”

The Role of Blockchain

Decentralized blockchain networks can work hand in hand with federated learning for AI algorithms to ensure that the data collected and analyzed is decentralized, easily verifiable and tamper-proof, so that healthcare providers can work with women to make better-informed decisions about their care.

Smart contracts executed on blockchain networks can automate payment processes, eliminating intermediaries and reducing costs associated with healthcare transactions, which is key for patients with lower incomes.

Blockchain can also solve another challenge in advancing women’s healthcare by using decentralized autonomous organizations (DAOs) to obtain financing for research to bridge the data gap.

For instance, Athena DAO issues calls for proposals in particular areas of women’s health research. The proposals are evaluated and the community’s token holders can then vote on them to allocate funds collaboratively.

Proposals that are accepted are linked to smart contracts, which are executed to release funding when certain research milestones are met. Research that develops profitable products or services reinvests into the DAO, creating a cycle of funding.

When it comes to investment, there is a large addressable market that has yet to be tapped into.

“From an investment standpoint the prospect for outsized returns is really significant,” Cepak said.

“Women spend 15 billion more dollars on out-of-pocket healthcare costs every year compared to men. So the potential for the category is huge, and as leaders in the space, we have to continue leaning into education and being that consistent voice.”

The Challenges of Integrating Technologies

But bringing technologies such as telehealth, AI and blockchain into healthcare is not an immediate panacea. There are technical, ethical, regulatory, and societal challenges.

  • Data quality and availability: As we have seen, women’s healthcare data can be fragmented, inconsistent, or unavailable, particularly in less developed regions. Ensuring comprehensive and high-quality datasets is crucial for accurate AI analysis and predictions.
  • Interoperability: Healthcare systems often use different software and data formats, making it difficult to integrate AI and blockchain solutions seamlessly. Interoperability is key to ensure that these technologies can communicate effectively with existing healthcare infrastructure.
  • Scalability: Blockchain technology, while secure, can face scalability issues. The large volume of health data generated can overwhelm blockchain systems, leading to slower processing times and higher costs.
  • Technical expertise: There may be a shortage of professionals in the healthcare sector capable of implementing and maintaining advanced technologies.
  • Data privacy: Women’s health data is particularly sensitive, and any breach could lead to significant ethical and legal consequences.
  • Bias and fairness: AI systems can inherit biases from training data, which can perpetuate existing disparities and inequalities. Ensuring that AI systems are fair and unbiased requires rigorous testing and validation.
  • Regulatory compliance: AI and blockchain technologies need to comply with complex healthcare regulations, which can be challenging to navigate as regulations may vary significantly between countries.
  • Acceptance and trust: Building trust among women and healthcare providers in these technologies is essential to drive adoption.
  • Digital divide: Access to advanced technologies can be uneven, with women in low-income or rural areas facing significant barriers.
  • Cultural sensitivity: Cultural factors often influence women’s health issues. AI and blockchain solutions need to be designed with this in mind to be effective and accepted in certain communities.
  • Cost and resources: The initial investment required to implement AI and blockchain technologies can be substantial, and healthcare institutions may struggle to allocate the necessary funds.

In the US, “one of the biggest challenges has been the fragmentation that digital health has created in the space as well as the regulatory environment making digital health a state-by-state execution,” Cepak said.

“You would think that there would be one definition of digital health in the US; that is not the case. It makes companies like Wisp have to be that much more creative in our delivery of care.”

Fostering trust in these technologies so that women will feel confident enough to use them can also present a challenge.

“There are so many barriers to adoption, so how do we build trust with women to use these digital health tools? Building trust is a really important piece of this puzzle,” said Joy Rios, founder of HIT Like a Girl Pod.

“Technology moves at the speed of trust,” Gee said. However, this “doesn’t mean that technology can enable everything that happens after that trust in that relationship is built. We leverage the in-person visit and that understanding of what’s happening in the whole family.”

“We need to think about where in-person matters and where technology is important,” Gee said, noting that as CEO of LSU Health, she observed during COVID-19 lockdowns that only 15 people used its AI-driven primary care platform over a period of three months because patients did not trust it with their personal information.

“We have to think about how these two things are melded, and often we too easily go to ‘oh there’s an app for that’, or ‘there’s a digital health solution for that’, but we don’t believe that we can address the true determinants of health, particularly for vulnerable Americans, just with technology—we’ve got to have both.”

The Bottom Line

The convergence of technologies such as AI and blockchain technologies offers new opportunities to revolutionize women’s health.

From personalized healthcare solutions and early disease detection to secure health data management and improved access to services, these technologies have the potential to transform the way women experience healthcare.

However, realizing this potential requires concerted efforts from policymakers, healthcare providers, technologists, and communities to overcome the complex challenges involved with women’s healthcare to ensure that these innovations are deployed ethically, equally, and with consideration for women’s autonomy and well-being.


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Nicole Willing
Technology Journalist
Nicole Willing
Technology Journalist

Nicole is a professional journalist with 20 years of experience in writing and editing. Her expertise spans both the tech and financial industries. She has developed expertise in covering commodity, equity, and cryptocurrency markets, as well as the latest trends across the technology sector, from semiconductors to electric vehicles. She holds a degree in Journalism from City University, London. Having embraced the digital nomad lifestyle, she can usually be found on the beach brushing sand out of her keyboard in between snorkeling trips.