Praise Ifenna Okwuba on the Future of AI-Powered Diagnostics in Healthcare

Praise Ifenna Okwuba, a data scientist working at the intersection of healthcare and artificial intelligence, has emphasized the growing role AI-powered diagnostics are expected to play in the future of healthcare, particularly in improving diagnostic accuracy and supporting better patient care.

As artificial intelligence continues gaining attention across the healthcare sector, diagnostic technologies powered by machine learning and advanced analytics are increasingly being viewed as important tools for addressing some of healthcare’s most persistent challenges. According to Okwuba, the ability of AI systems to analyze large volumes of clinical information and generate timely insights could significantly improve how diseases are identified, assessed, and managed.

He noted that healthcare systems generate enormous amounts of clinical and operational data every day, much of which remains underutilized. With advances in artificial intelligence, however, healthcare providers are gaining new opportunities to extract meaningful insights from this information and use them to support more informed diagnostic decisions.

“AI-powered diagnostics have the potential to significantly improve how diseases are detected and evaluated,” Okwuba said. “By combining clinical expertise with machine learning and high-quality data, healthcare providers can gain faster insights, improve diagnostic accuracy, and ultimately deliver better outcomes for patients.”

Okwuba’s perspective is informed by more than five years of experience working with healthcare data, public health programmes, and advanced analytics. His work has focused on transforming complex healthcare information into actionable insights that support evidence-based decision-making and improve healthcare outcomes.

He previously worked at Caritas Nigeria, where he served as a Strategic and Information Analyst between 2019 and 2022 before advancing to the role of Senior Strategic and Information Analyst from 2022 to 2023. During that period, one of his notable achievements includes designing data collection frameworks that improved data completeness by 30%, while supporting the management of more than 50,000 patient records and strengthening information systems used in HIV-related healthcare programmes.

His expertise is supported by a combination of professional experience and academic achievement. Okwuba earned a Bachelor of Science degree in Computer Science from the University of Benin in 2021 and later completed a Master of Science degree in Data Science at the University of Chester in the United Kingdom in 2024.

Currently serving as a Data Science Consultant at AMDARI in Canada, Okwuba works on healthcare-focused artificial intelligence and analytics initiatives involving large-scale clinical datasets. His work includes developing secure data systems, analyzing healthcare information, and supporting AI-driven solutions designed to improve operational efficiency and patient care outcomes.

Related News Startup leverages tech to predict medical risks

Firm urges healthcare providers to prioritise quality service

NDPHC deploys AI to improve power plant management

Drawing on expertise in Python, SQL, TensorFlow, Power BI, predictive modelling, and clinical data analytics, Okwuba’s work focuses on developing data-driven solutions that support healthcare decision-making and advance the practical application of artificial intelligence within clinical environments.

According to Okwuba, one of the most promising applications of artificial intelligence lies in diagnostics, where AI systems can help healthcare professionals identify patterns that may be difficult to detect through conventional methods alone.

His perspective is also informed by his involvement in an ongoing AI-driven diagnostics project at AMDARI focused on reducing pathology backlogs through automated breast histopathology slide triage. The initiative applies machine learning, data preprocessing, and transfer learning techniques to support pathologists in prioritizing cases more efficiently, with targets that include a 30% reduction in benign slide reviews and a 20% decrease in diagnostic turnaround times.

The project reflects the growing role of artificial intelligence in helping healthcare professionals manage increasing diagnostic workloads while maintaining quality and accuracy.

“The future of diagnostics will be shaped by how effectively healthcare organizations combine artificial intelligence with clinical expertise,” Okwuba said. “When implemented responsibly, AI can help clinicians make faster and more informed decisions while improving efficiency and patient outcomes.”

Okwuba believes the future of diagnostics will depend not only on technological advancement but also on responsible implementation, high-quality data, and collaboration between healthcare professionals and technology experts.

As healthcare organizations continue exploring artificial intelligence as a tool for improving diagnostic accuracy and efficiency, Okwuba believes the technology will increasingly become an important component of modern healthcare delivery. He argues that the most successful AI-powered diagnostic systems will be those designed to complement clinical expertise while helping healthcare providers deliver faster, more accurate, and more effective patient care.