Revolutionizing Healthcare: The 10 Best AI-Based Apps of 2024

AI in Healthcare

Nowadays we all have become very dependent on AI. AI has spread its wings in almost every field of our life. AI has always been a hot topic of debate and has always received a good amount of limelight due to its rapid advancement. AI has been growing and is being used in almost every field of life. In today’s era, AI has become an important part of the healthcare industry as well. AI has been actively taking part in every sphere of the healthcare industry, be it the diagnosis or be it the treatment of the ill. As of today, AI is primarily utilized to increase speed and accuracy in the healthcare realm. Some of the current uses of AI in this field include:

  • Diagnosing Patients: AI algorithms analyze medical imaging data, such as X-rays, MRIs, and CT scans, to assist healthcare professionals in accurate and swift diagnoses.
  • Transcribing Medical Documents: Automatic Speech Recognition (ASR) technology employs advanced algorithms and machine learning models to convert spoken language into written text, providing a more efficient and accurate method for documenting medical information.
  • Drug Discovery and Development: AI accelerates the drug discovery process by analyzing vast datasets to identify potential drug candidates and predict their efficacy.
  • Administrative Efficiency: AI streamlines administrative tasks, such as billing and scheduling, reducing paperwork and improving overall operational efficiency within healthcare organizations.
  • Precision medicine: AI is used to produce personalized treatment plans for patients that take into account such factors as their medical history, environmental factors, lifestyles, and genetic makeup. 

AI already plays an important role in healthcare, and it has a very bright future as capabilities continue to advance and grow. It is positioned to improve patient outcomes, increase safety, reduce human error, and reduce costs associated with healthcare, along with many other things.


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Top 10 AI applications in healthcare industry

1. IBM Watson Health

It is a prominent application of artificial intelligence in healthcare. It combines AI, machine learning, and natural language processing to analyze vast amounts of medical data and assist healthcare professionals in making more informed decisions.  It uses AI to assist doctors in identifying personalized, evidence-based treatment options by analyzing vast amounts of medical literature, clinical trial data, and patient records. By harnessing the power of AI and cognitive computing, IBM Watson Health aims to transform healthcare delivery, empower healthcare professionals with data-driven insights, and ultimately improve patient outcomes.

2. Google DeepMind Health

This AI app is a division of DeepMind, an artificial intelligence research lab owned by Google. DeepMind Health focuses on developing AI-powered solutions to address complex healthcare challenges and improve patient care.  It focuses on predicting protein folding, which is crucial for understanding diseases and developing new drugs. This technology can help in drug discovery and protein structure prediction.

 Some applications of Google DeepMind Health are:

  1. Medical Image Analysis: DeepMind Health has worked on AI models to analyze medical images, such as retinal scans, to detect and diagnose conditions like diabetic retinopathy and age-related macular degeneration.
  2. Patient Monitoring and Predictive Analytics: DeepMind Health has developed AI systems to analyze patient data and predict deterioration. 

3. Zebra Medical Vision

Zebra Medical Vision is a leading company that uses artificial intelligence and machine learning to develop advanced medical imaging analytics. Their AI-powered platform aims to assist radiologists and healthcare professionals in detecting and diagnosing various medical conditions. 

Some key applications of Zebra Medical Vision include:

  1. Quantitative Imaging Biomarkers: Zebra Medical Vision’s platform can automatically extract quantitative measurements and biomarkers from medical images. This allows for objective and standardized assessments of conditions like osteoporosis, fatty liver, and coronary artery calcifications.
  2. Triage and Prioritization: Zebra Medical Vision’s algorithms can assist in triaging and prioritizing medical cases based on the severity of detected abnormalities. 
  3. Longitudinal Tracking: Zebra Medical Vision’s platform enables the tracking and comparison of medical images over time. This is particularly useful for monitoring disease progression, evaluating treatment response, and identifying potential changes in a patient’s condition.
  1. Butterfly Network

Butterfly Network is a company that specializes in developing handheld, pocket-sized ultrasound devices powered by artificial intelligence. Their innovative technology combines hardware and software to provide accessible and high-quality medical imaging solutions. 

The Butterfly iQ, their flagship product, is an ultrasound device that connects to a mobile device or tablet. It incorporates advanced AI algorithms and machine learning to deliver real-time imaging capabilities for a wide range of medical applications. Butterfly Network’s technology allows healthcare providers to store, access, and share ultrasound images securely through their cloud-based platform. This facilitates collaboration, remote consultations, and longitudinal tracking of patient imaging data. The combination of portability, AI-powered imaging, and cloud connectivity positions Butterfly Network’s technology as a promising solution for point-of-care ultrasound. It empowers healthcare professionals with advanced imaging capabilities and has the potential to improve patient outcomes, particularly in resource-limited or remote settings.

5. Aidoc

Aidoc is a leading provider of AI-powered radiology solutions that aim to enhance the accuracy and efficiency of radiology diagnoses. This platform uses deep learning algorithms to analyze medical images and assist radiologists in detecting and prioritizing critical findings.

  1. Advanced Imaging Analytics: Aidoc’s AI algorithms analyze medical images, such as CT scans, MRIs, and X-rays, to identify and flag abnormalities and critical findings. 
  2. Workflow Prioritization: Aidoc’s platform integrates seamlessly into radiology workflows, providing a triage system that automatically prioritizes cases based on the urgency of detected abnormalities. This helps radiologists manage their workload efficiently and ensures that critical cases receive prompt attention.
  3. Quality Improvement: Aidoc’s algorithms not only aid in identifying abnormalities but also provide quality improvement insights by detecting common imaging errors or discrepancies. 

6. Tempus

Tempus is a technology company that utilizes artificial intelligence and data analytics to drive advancements in precision medicine. The company’s mission is to empower healthcare professionals with data-driven insights and tools to deliver personalized care and improve patient outcomes. Tempus focuses on building an extensive library of clinical and molecular data, along with advanced analytics capabilities, to enable precision medicine in various areas. Tempus aims to bridge the gap between technology and healthcare, leveraging AI and data analytics to unlock the potential of precision medicine. By combining molecular and clinical data, they strive to enable more personalized and targeted therapies, ultimately improving patient outcomes.

7. Path AI

Path AI is a company that specializes in applying artificial intelligence and machine learning to pathology. Their goal is to improve accuracy and efficiency in diagnosing diseases through advanced image analysis and data-driven insights.

The main applications of  Path AI’s technology are:

  1. Digital Pathology: Path AI digitizes and analyzes pathology slides using high-resolution scanning technologies. This allows for the creation of a digital pathology repository that can be accessed and analyzed using AI algorithms.
  2. Disease Diagnosis and Classification: Path AI’s algorithms assist pathologists in accurately diagnosing and classifying diseases, such as cancer. By analyzing digital pathology images, the algorithms can detect patterns, identify biomarkers, and provide quantitative measurements, helping pathologists make more informed diagnoses.
  3. Prognostic and Predictive Analytics: Path AI’s technology can analyze digital pathology images and patient data to provide prognostic insights. 
  4. Drug Development and Research: PathAI collaborates with pharmaceutical companies and researchers to accelerate drug development and clinical trials. 

Path AI aims to enhance pathology practices by integrating AI and machine learning into the interpretation of digital pathology images. 

8. Gauss Surgical

Gauss Surgical is a healthcare technology company that specializes in developing AI-driven solutions for surgical and perioperative care. Their focus lies in leveraging data analytics and artificial intelligence to enhance patient safety, improve surgical outcomes, and optimize the surgical workflow.

Key aspects and applications of Gauss Surgical’s technology include:

  1. Blood Loss Monitoring: Gauss Surgical’s AI algorithms analyze real-time video footage from surgical procedures to accurately estimate and monitor blood loss. This helps healthcare providers proactively manage bleeding during surgery and make informed decisions regarding transfusions and interventions.
  2. Real-time Decision Support: Gauss Surgical’s platform offers real-time feedback and decision support to surgeons and anesthesiologists during surgical procedures. This assists in optimizing surgical techniques, managing blood loss, and improving patient safety in the operating room.

Gauss Surgical’s AI-driven solutions aim to enhance surgical care by providing objective, data-driven insights and decision support. 


OWKIN is a company that harnesses the power of artificial intelligence and machine learning to transform medical research and improve healthcare outcomes. They specialize in building collaborative platforms and advanced analytics tools that enable data sharing and analysis while ensuring privacy and security. OWKIN’s innovative approach to collaborative and privacy-preserving AI in healthcare research has the potential to revolutionize medical discoveries and drive advancements in precision medicine

Key aspects and applications of OWKIN’s technology include:

  1. Federated Learning: OWKIN’s platform enables collaboration among healthcare institutions and researchers by utilizing federated learning. This approach allows the sharing and analysis of data while keeping it decentralized and secure, maintaining data privacy and compliance with regulations.
  2. AI Models for Medical Research: OWKIN develops AI models that can analyze diverse datasets, including clinical data, imaging data, and genomics data. These models assist researchers in extracting meaningful insights, identifying patterns, and discovering new correlations to advance medical research.

10. Prognos

Prognos is a healthcare analytics company that leverages artificial intelligence and advanced analytics to transform patient data into actionable insights. They specialize in applying data-driven approaches to improve disease identification, treatment decisions, and patient outcomes.

Key aspects of Prognos’ technology include:

  1. Predictive Analytics: Prognos’ AI algorithms analyze large volumes of patient data, including lab results, claims data, and EHR data, to identify patterns and predict disease outcomes. This helps healthcare providers intervene earlier, personalize treatment plans, and improve patient management.
  2. Disease Registry and Stratification: Prognos’ platform enables the creation of disease registries by aggregating and analyzing patient data. This helps identify high-risk populations, stratify patients based on disease severity, and facilitate targeted interventions and preventive measures.
  3. Real-world Evidence Generation: Prognos analyzes real-world data to generate evidence on treatment outcomes, disease progression, and the effectiveness of interventions. This real-world evidence can support clinical research, inform clinical guidelines, and facilitate evidence-based decision-making.

By harnessing the power of AI and analytics, Prognos aims to unlock the value of healthcare data and empower healthcare organizations with actionable insights.