Applications of AI in
Healthcare 2025–2026
Complete Study Bundle | Full
Course Notes, Clinical Use
Cases, Diagnostics, Machine
Learning Models, Medical Data
Analysis, Ethics, Policy
Insights & Exam-Ready
Summaries | Latest Updated
Medical AI Study Guide
two main benefits of AI in medical imaging - Answer✅improves accuracy+ speed of diagnosis,
reduces workload/ stress on human specialists
, two main challenges of AI in medical imaging - Answer✅accuracy/ reliability and no bias, and
ethical/transparent use with privacy safeguards
4 main types of AI used in medical image analysis - Answer✅CNNs, RNNs, SVMs, decision trees
CNN, RNN, SVM - Answer✅convolutional neural networks, recurrent neural networks, support
vector machines
what are CNNs? - Answer✅a type of deep learning algorithm consisting of several interconnected
neuron layers that identify image patterns and features to segment, detect, and classify images
what are RNNs? - Answer✅deep-learning algorithm used for sequential data analysis, used for image
reconstruction or analysis of medical signals
what are SVMs? - Answer✅machine learning algorithm used for classification tasks
decision trees - Answer✅machine learning algorithm used for classification and regression,
partitioning input data into subsets and to predict condition likelihood
detection/diagnosis of breast cancer/ lung cancer/ brain tumors: AI - Answer✅CNNs analyze digital
mammograms/chest CT scans/MRI scans and detect early signs and types of cancers quicker and
much more accurately than human specialists
4 main conditions CNNs can identify quicker than human specialists: - Answer✅lung cancer, breast
cancer, brain tumors, and diabetic retinopathy
how can AI help with personalized treatment planning or disease progression monitoring? -
Answer✅can analyze individual patient data and develop maximum improvement plans, or analyze
data to track changes in disease severity or treatment response and effects
which 6 stages of drug discovery can AI help with? - Answer✅target identification, lead discovery,
lead optimization, preclinical testing, clinical testing, and regulatory approval
what are the main algorithms used in drug discovery? how? - Answer✅machine learning: predictions
and analyzing of data
4 benefits of ai in drug discovery - Answer✅more efficient development, more accurate design,
personalized treatment options, reduced costs
4 limitations of AI in drug discovery - Answer✅data quality/ availability, ethical concerns,
integration/ implementation issues, and regulatory challenges (validation, safety)
3 main AIs in drug discovery - Answer✅Atomwise, Insilico Medicine, BenevolentAI
Atomwise - Answer✅uses AI to predict activity of potential drug candidates against specific targets,
using deep learning algorithms to analyze large databases of chemical compounds: ebola, cystic
fibrosis, multiple sclerosis
Insilico Medicine - Answer✅uses AI to design new drugs for many diseases, using deep learning
algorithms to analyze large amounts of biological data and predict potential efficacy: Alzheimer's,
idiopathic pulmonary fibrosis
Benevolent AI - Answer✅uses AI to analyze large amounts of clinical trial and scientific publication
data, using natural language processing and machine learning algorithms to identify key information
from this data: Parkinson's, sarcopenia
CDSS is used for what? - Answer✅assist in making clinical decisions
Healthcare 2025–2026
Complete Study Bundle | Full
Course Notes, Clinical Use
Cases, Diagnostics, Machine
Learning Models, Medical Data
Analysis, Ethics, Policy
Insights & Exam-Ready
Summaries | Latest Updated
Medical AI Study Guide
two main benefits of AI in medical imaging - Answer✅improves accuracy+ speed of diagnosis,
reduces workload/ stress on human specialists
, two main challenges of AI in medical imaging - Answer✅accuracy/ reliability and no bias, and
ethical/transparent use with privacy safeguards
4 main types of AI used in medical image analysis - Answer✅CNNs, RNNs, SVMs, decision trees
CNN, RNN, SVM - Answer✅convolutional neural networks, recurrent neural networks, support
vector machines
what are CNNs? - Answer✅a type of deep learning algorithm consisting of several interconnected
neuron layers that identify image patterns and features to segment, detect, and classify images
what are RNNs? - Answer✅deep-learning algorithm used for sequential data analysis, used for image
reconstruction or analysis of medical signals
what are SVMs? - Answer✅machine learning algorithm used for classification tasks
decision trees - Answer✅machine learning algorithm used for classification and regression,
partitioning input data into subsets and to predict condition likelihood
detection/diagnosis of breast cancer/ lung cancer/ brain tumors: AI - Answer✅CNNs analyze digital
mammograms/chest CT scans/MRI scans and detect early signs and types of cancers quicker and
much more accurately than human specialists
4 main conditions CNNs can identify quicker than human specialists: - Answer✅lung cancer, breast
cancer, brain tumors, and diabetic retinopathy
how can AI help with personalized treatment planning or disease progression monitoring? -
Answer✅can analyze individual patient data and develop maximum improvement plans, or analyze
data to track changes in disease severity or treatment response and effects
which 6 stages of drug discovery can AI help with? - Answer✅target identification, lead discovery,
lead optimization, preclinical testing, clinical testing, and regulatory approval
what are the main algorithms used in drug discovery? how? - Answer✅machine learning: predictions
and analyzing of data
4 benefits of ai in drug discovery - Answer✅more efficient development, more accurate design,
personalized treatment options, reduced costs
4 limitations of AI in drug discovery - Answer✅data quality/ availability, ethical concerns,
integration/ implementation issues, and regulatory challenges (validation, safety)
3 main AIs in drug discovery - Answer✅Atomwise, Insilico Medicine, BenevolentAI
Atomwise - Answer✅uses AI to predict activity of potential drug candidates against specific targets,
using deep learning algorithms to analyze large databases of chemical compounds: ebola, cystic
fibrosis, multiple sclerosis
Insilico Medicine - Answer✅uses AI to design new drugs for many diseases, using deep learning
algorithms to analyze large amounts of biological data and predict potential efficacy: Alzheimer's,
idiopathic pulmonary fibrosis
Benevolent AI - Answer✅uses AI to analyze large amounts of clinical trial and scientific publication
data, using natural language processing and machine learning algorithms to identify key information
from this data: Parkinson's, sarcopenia
CDSS is used for what? - Answer✅assist in making clinical decisions
