AI in Life Sciences Innovation in Research and Healthcare

To look into the possibilities of AI, one should take a closer look at its very
concepts, which lie at the foundation of the AI systems:
Machine Learning falls under AI and can refer to systems that learn and
enhance themselves with experience without being directly programmed. ML
algorithms analyze huge amounts of data and understand the patterns, making
data-driven conclusions. The more data are available on such models, the more
precise they become, and as such they are highly suitable to applications such
as individualized medicine and diagnostics.
NLP is something that allows computer to interpret understand and generate
human language. This is especially essential to AI systems working with users
through natural language, e.g., voice-based assistants or automatic
transcription software. NLP also plays a vital role when analyzing a massive
amount of unstructured information, such as medical records or research
papers, and transforming it into usable information.
Robotics powered by AI is where machines complete a task with or without
human supervision. These systems are adopted in such areas such as the
surgical department where the robots can help out or even carry out minute
procedures and in manufacturing drugs where automation is essential to
efficiency.
The AI-enabled computer vision can enable machines to see and interpret
visual information, just like humans. In diagnostic imaging, it plays a role in
finding abnormalities in X-rays, MRIs or CT scans, which can be evaluated as
a game-changer in the early diagnosis of disease, e.g. in the detection of
cancerous cells in a tissue sample.