Artificial intelligence (AI) is transforming prosthodontics by enhancing efficiency, accuracy, and patient satisfaction. This review explores the latest advancements and innovative applications of AI across various subspecialties, including fixed, removable, implant, and maxillofacial prosthodontics. AI is revolutionizing multiple aspects of prosthodontic care, from diagnosis and decision-making to treatment planning and outcome prediction. Its applications extend to tooth shade selection, restoration design, precise tooth preparation, optimization of casting and manufacturing, implant design, robotics, and predicting facial changes in patients with removable prostheses. Additionally, AI plays a crucial role in assessing treatment outcomes for temporomandibular disorders, further contributing to improved oral health care. Despite its potential to enhance precision and streamline dental procedures, widespread implementation is hindered by the limited availability of extensive datasets. Overcoming this challenge will be essential for maximizing AI’s impact on prosthodontic practice.
Key words: artificial intelligence, machine learning, deep learning, robotics, CAD/CAM
Prosthodontics is rapidly evolving with
advancements in technology, materials, and
digital innovations, with artificial intelligence
(AI)
and robotics significantly enhancing
clinical practice, education, and research.
AI, first conceptualized in 1943 and formally
named by John McCarthy in 1956, refers to
machine programs capable of logical reasoning
and cognitive tasks. With advancements in
computing, big data, and machine learning
(ML), AI has become an essential tool in
various medical fields, including dentistry1. A
specialized branch of ML, deep learning (DL),
utilizes convolutional neural networks (CNNs) to
analyze complex datasets, making it particularly
useful in dentistry for improving image analysis,
optimizing workflows, and enhancing treatment
precision by processing vast amounts of
clinical, imaging, and proteomic data2. In
Prosthodontics, AI-powered CAD/CAM software
enables precise tooth realignment for denture
fabrication, ensures superior aesthetics and
function, enhances color-matching techniques for seamless restorations, and improves implant
planning by integrating intraoral scans with CAD
programs for more accurate implant placement
and prosthetic design. AI is time-saving and
revolutionizes dental care by minimizing costs,
providing customized, proactive treatment, and
integrating healthcare services to enhance
overall patient welfare3.
Traditionally, prosthodontic restoration has
heavily depended on the expertise of dentists and
technicians, requiring labor-intensive manual
techniques that leave room for human error. While
modern advancements have mitigated these
errors to some extent, the integration of AI has the
potential to transform the entire prosthodontic
workflow, from diagnosis to treatment planning
and execution. AI offers various attributes that
enhance precision, efficiency, and predictability
in prosthodontic restoration.4
These attributes include:
Artificial intelligence is transforming dentistry
by improving diagnosis, treatment planning,
and patient care. Machine learning algorithms
analyze dental images to detect caries,
periodontal disease, and oral pathologies with
high accuracy. In orthodontics, prosthodontics,
and implantology, AI optimizes treatment
planning, enhances digital smile design, and
improves the precision of CAD/CAM restorations.
AI also aids in endodontics by identifying root
canal morphology and periapical infections,
ensuring better treatment outcomes.
Beyond clinical applications, AI enhances
patient management and education. AI
powered chatbots assist with scheduling and
post-operative care, while tele-dentistry enables
remote diagnosis. In research and training, AI
analyzes large datasets to improve treatment
protocols and supports simulations for dental
students. Despite challenges like data privacy
concerns, AI is making dentistry more efficient,
precise, and patient-focused6.
Prosthetic dentistry is the art and science of
dentistry that deals with the diagnosis, treatment
planning, rehabilitation and preservation of
the oral structures function, comfort, aesthetics
and health of patients with clinical problems
associated with missing or deficient teeth and
oral and maxillofacial tissues. Prosthodontics
mainly focuses on the treatment and fabrication
of removable and fixed dental prosthesis,
preparation of finishing margins alongside
the tooth for better extension and fitting of the
prosthesis, implant procedure and construction
of a maxillofacial prosthesis. Maintenance of
proper maxillomandibular relations, selection of
tooth shade for better aesthetics. AI can be very
advantageous in various methods of treatment
protocol7.
The main areas of focus for AI in prosthodontics
are:
Diagnosis and Treatment Planning
The application of artificial intelligence for
accurate diagnosis in Prosthodontics is based on
AI-based imaging analysis. Intra oral scanners
and CBCT scans generate large amounts of
digital data, AI algorithms can extract valuable
information and assist in diagnosis. Machine
learning (ML) makes these functions possible
by teaching computers rules based on data
and identifying inherent statistical patterns and
structures in the data and thus help in analyzing
any anomalies in the tooth structure.
AI-assisted treatment planning algorithms play
a vital role in simplifying and optimizing the
treatment planning process. These algorithms
create personalized treatment regimens by
analyzing patient data, such as clinical records,
diagnostic pictures,
and patient-specific
characteristics, using artificial intelligence
approaches. AI algorithms can identify patterns
and correlations in a big dataset to establish
the best course of action for each patient by
utilizing machine learning and data mining.
To create individualized treatment plans and
optimize treatment outcomes, factors such as
patient’s current state of oral health, aesthetic preferences, functional requirements, and
anatomical concerns are considered.8
Fixed Prosthodontics
1. The Digital Smile Design
Artificial intelligence (AI) is increasingly being
integrated into the domain of smile design,
bringing forward numerous benefits and
advancements. The AI algorithms possess
the capability to meticulously analyze various
aspects of facial features, including symmetry,
lip line, tooth shape, and size, to generate
optimal smile designs. This technological
advancement significantly enhances both the
precision and efficiency of the design process,
thereby enabling dental practitioners to deliver
treatments that are not only aesthetically
pleasing but also functionally effective. One of
the AI-based systems, such as the Visagi Smile
concept, leverages Machine Learning techniques
to establish a relationship between facial
perception and personality traits in the context
of smile design. This approach facilitates the
creation of highly personalized treatment plans
that take into account the unique characteristics
of each patient, ultimately leading to more
tailored and satisfactory outcomes.1
2. The Tooth Shade Selection
The shade guides for tooth shade selection in
clinical prosthodontics are currently available
in countless types and capabilities. Along
the classical Vita Classical Shade Guide, the
shade-matching spectrophotometers, intraoral
electronic devices like Vita Easyshade (Vita
Zahnfabrik, Bad Säckingen, Germany), the
ShadeEye NCC Chroma Meter (Shofu Dental,
Menlo, CA, USA), the iTero Element (Align
Technology, Inc., San Jose, CA, United States),
computer-aided shade selection software, colorimetric systems, hybrid devices, and mobile
applications are some of the past and current
options for an accurate assessment of tooth
color and shade9.
3. The Mapping of the Preparation
Finishing Line
The use of AI in mapping the preparation finishing
line in fixed prosthodontics promises significant
precision and efficiency in the last decade. AI
algorithms, particularly those based on ML and
DL, have been developed to accurately detect
and map the preparation finishing line of dental
preparations. These algorithms analyze digital
impressions or intraoral scans to identify the
exact margins of the preparation, ensuring a
precise fit for the dental crowns and bridges.10
4. The Automated Tooth Preparation
Recently, Perceptive, a company based in
Boston (MA, USA), introduced an AI-driven
robotic system designed for dental procedures,
including the preparation of teeth for dental
crowns. This innovative robot utilizes advanced
optical coherence tomography (OCT) and AI
programming to create detailed 3D maps of
the teeth, which are then analyzed by AI to plan
the tooth preparation. The system can complete
a procedure that typically takes several hours
in just about 15 min. Further benefits consist of
increased precision and accuracy compared to
that matched by the human hands, resulting in
better fitting crowns and bridges11.
5. Prosthesis Design and Fabrication
The fabrication and delivery of the finest
removable and fixed prostheses is the primary
expectation of prosthodontics. CAD and CAM
systems combined with a three-dimensional
digital workflow have revolutionized the practice
of dentistry. An initial intra-oral scan is sent
to the CAD/CAM software, which designs,
manufactures, prints, or mills the prosthesis.
CAD/CAM is useful to manufacture inlays, onlay,
crowns, and bridges. This saves time, resources,
and energy for both prosthodontics and patients.
This also reduces the chances of human error in
the final prosthesis.12
AI-Driven Workflow in Modern Dental Practice
In
modern dental practice, AI co-piloting
enhances the dentist’s role by acting as an
intelligent assistant. While the dentist remains
the primary decision-maker, AI supports the
process by analyzing vast amounts of data
and extracting insights from comprehensive
knowledge bases. This collaboration leads to
more informed decision-making by providing
evidence-based recommendations, predicting
treatment outcomes, identifying potential risks,
and personalizing care strategies. As a result,
AI integration optimizes clinical efficiency and
improves patient care.13
Removable Prosthodontics
1. Predicting facial changes before
treatment
AI models have been employed to forecast facial
alterations in edentulous individuals who are
going to undergo complete denture treatment.
Following the delivery of the prosthesis, the
model successfully anticipated alterations in the
facial soft tissue14.
Backpropagation Neural Network (BPNN) to
create an AI model that effectively forecasted
the surface roughness and microhardness of
four denture tooth materials when subjected
to four distinct liquids. Predicting surface
roughness and microhardness based on
particular characteristics can help in choosing
suitable denture materials and fostering their
performance15.
Designing of Removable partial dentures
AI has been employed in the design of Removable
Partial Dentures (RPDs), beginning with the
identification of the position of the missing teeth,
categorization of the prosthetic condition of the
remaining teeth, and analysis of the occlusion.
AI applications translate two dimensional RPD
design diagrams into a structured tree format
utilizing CAD/CAM technology to generate three
dimensional RPD frameworks16.
Designing Removable Partial Dentures (RPDs) is
a complex task guided by a set of established
rules. To streamline this process, a novel logic
based RPD design software called AiDental
was developed. The AiDental RPD Designer
utilizes algorithm-based software with basic AI
functionality, acting as a decision-making tool
for RPD design. Its algorithms incorporate the
principles of RPD design, allowing the software
to process user input and automatically generate
accurate RPD frameworks.17
Implantology
Assist in diagnosis and Treatment
Planning
AI algorithms, trained on vast datasets of
images, possess the capability to analyze vast
amounts of patient data, including radiographic
images, three-dimensional scans, and clinical
records, and also accurately identify and
classify dental pathologies, bone structures, and anatomical landmarks. This capability is crucial
for the precise placement of dental implants,
ensuring optimal integration with the patient’s
existing bone structure. For instance, AI systems
can analyze CBCT scans to detect the quality
and quantity of bone, which is essential for
determining the feasibility of implant placement
and planning the surgical approach.
Detection/Recognizing Implant Type/
Brand
Different implant brands have various
abutments and prosthetic components, making it
challenging to identify them when complications
arise, especially if the original clinician is
unavailable. Accurate identification requires
information about the implant manufacturer,
diameter, length, platform, and abutment
type. AI-based implant brand detection offers
a promising solution to this problem. Studies,
such as a multi-center study by Park et al.
involving 156,965 radiographs, have shown high
accuracy in identifying dental implant systems
(DIS). However, differences in datasets, CNN
models, and implant brands lead to varying
results18. To improve accuracy, it is essential to
expand datasets and develop regional-based
deep learning models while maintaining ethical
standards19.
Development of New Implant Designs
AI models have been used to enhance dental
implant design by predicting how implants
manage stress at the bone connection. For
example, Li et al. developed an AI model that
reduced stress at the implant-bone interface by
36.6% compared to traditional FEA methods.
Roy et al. combined neural networks and genetic
algorithms to optimize implant geometry, while
Zaw et al. applied AI to measure the elasticity
of the bone-implant interface. Although these
studies show promise, more research involving
in vitro, animal, and clinical studies is needed to
improve practical applications20.
Prediction of Treatment Outcomes in
Implantology
AI algorithms have been used to predict the
risk of dental implant failure, helping dentists
identify high-risk patients and adjust treatment
plans.21 Huang et al. developed three models—a
clinical model, a radiographic model, and a
combined model—with the combined model
showing the best performance in predicting
implant failure within five years. Similarly, Zhang
et al. developed a model using dental X-rays,
achieving 87% accuracy by analyzing bone
loss around implants. While these models are
promising, more long-term studies are needed
to ensure their reliability in practice22.
Robotic Implant Surgery
The integration of robotics and AI in dentistry,
known as “dentronics,” aims to enhance precision
in dental implant placement. Accurate surgical
placement is essential to avoid complications
during both surgical and prosthetic phases.
In 2017, the FDA approved a robotic surgical
assistant for dental implant placement.11
The dentist plans the implant position using
CBCT scans, and the robotic arm performs
the surgery while the dentist monitors and can
adjust angulation in real-time. In the same year,
a successful case in China involved a robot
placing two implants in a patient without dentist
intervention. AI can further advance dentronics
by analyzing large patient datasets to improve
diagnosis and treatment planning.23
Detection of fractured implants
AI has shown great potential in detecting
fractured dental implants. Dong-Woon Lee et
al study evaluated VGGNet-19, GoogLeNet
Inception-v3, and automated DCNN (Deep
Convolutional Neural Network) architectures, all
of which demonstrated acceptable accuracy in
identifying and classifying fractured implants. Among them, automated DCNN performed the
best, using periapical radiographic images.
Further clinical validation is needed.24
Maxillofacial Prosthodontics
Coloration Techniques for Maxillofacial
Prostheses
The pigmentation of maxillofacial prostheses
is vital in attaining a lifelike and authentic
appearance for those in need of facial repair.
Commercially available computerized colour
matching system (e-skin) has enabled good
colour matching. Creating a skin colour
matching technique based on real-time Deep
earning (DL) might improve the accessibility
and affordability of colouring support for
maxillofacial prostheses.25
Skin tissue engineering
Skin tissue engineering is a contemporary
medical practice that aims to create bioprinter
biomaterial-based synthetic skin grafts. This
cutting-edge approach to wound regeneration
attempts to create skin replacements that work
as bioactive dressings, improving the wound’s
functionality.14
AI-Enhanced Techniques in Obturator
Fabrication
Recent research shows progress in using AI
to design and fabricate obturators, aiming to
improve accuracy, reduce fabrication time, and
enhance the quality of life for maxillofacial
patients. Ali I.E. et al. evaluated four pre-trained
CNN models (VGG16, Inception-ResNet-V2,
DenseNet-201, and Xception) to recognize seven
prosthodontic scenarios related to the maxilla,
including conditions like cleft palate and various
types of maxillectomy. All models achieved over
90% accuracy, with Xception and DenseNet-201
performing slightly better, reaching up to 95%
accuracy. These results demonstrate the potential of AI in dental image analysis, automated
diagnosis, and prosthesis design.26
Advancements in eye Prosthesis
Fabrication Using AI
“Smart reading glasses,” which are voice
activated gadgets that can be attached to any
pair of glasses, are designed primarily to help
blind and visually challenged people. It can
quickly read text from a book, smartphone
screen, or any other surface, identify faces,
work more effectively, and help its user lead
an independent life. “Bionic eye,” created in
the United States, utilizes artificial intelligence
to help patients who have lost their sight see
without surgery5.
The Role of AI in TMJ Disorder
Management
Diagnosis and treatment planning
Within the domain of prosthetic rehabilitation
for temporomandibular joint (TMJ) disorders,
the utilization of Artificial Intelligence (AI)
techniques offers multifaceted benefits. In the
diagnostic phase, AI, particularly machine
learning algorithms, proves instrumental in
assimilating and interpreting extensive patient
data, facilitating a nuanced and early detection
of TMJ disorders. This data-driven approach
enhances the accuracy of diagnosis and sets the
foundation for targeted interventions.
Prosthetic Rehabilitation
In the arena of prosthetic rehabilitation, AI
contributes significantly to the customization
of devices. Machine learning algorithms
delve into patient-specific data, discerning
unique anatomical features and functional
requirements. This tailored approach ensures
the design and fabrication of prosthetic devices
that align precisely with individual needs, fostering enhanced comfort and functionality.28
Robots for treating TMJ disorders
The Waseda Asahi Oral-Rehabilitation Robot
No. 1 (WAO1) is an oral rehabilitation robot
developed by Waseda University in Japan. It
consists of a headrest-equipped body, two robotic
arms with six degrees of freedom, a control
box, a computer, and an automated massage
system. The robot massages the patient’s face,
including facial tissues, masticatory muscles
(masseter and temporalis), and oral structures
like the parotid gland and duct. Controlled by
a computer, it helps treat conditions such as
dry mouth and temporomandibular joint (TMJ)
disorders.11
Limitations of AI
Similar to any other technology, AI has its own
set of limitations and boundaries. AI technology
has not been completely understood owing to its
complexity, and it has the ability to autonomously
change its behaviour.7
Any fault in the accumulation, assessment, or
assortment of data can lead to substantial errors
in AI programs. Hence, the information and data
provided to AI must be correct, authentic, and
accurate at any given time. Therefore, AI models
and software require regular updates and
upgrades. AI processes large amounts of data
quickly, requiring high computational power.
This can be a potential barrier to AI productivity
because quantum computing is expensive and
unavailable for common use. Interpreting AI
results can pose challenges because of the
generalization of similar techniques across
various conditions. Prosthodontics involves
rehabilitation of the patient using prosthetic
materials; therefore, any miscalculation can lead
to unfavourable and disapproving outcomes or results.9
Ethical and legal considerations challenge
the growth of AI. Factors such as privacy, data
protection, informed consent, autonomy, social
gaps, justice, empathy, and safety must be
considered before using full-scale AI in medical
healthcare systems.18
It can be concluded that the use of artificial
intelligence are of immense use in dentistry, in
general but for prosthodontics it has a broader
role to play. AI is of greater application in
removable, fixed, maxillofacial, and implant
prosthodontics for its precision and accuracy. The
functionality and acceptance of prosthodontic
treatment are enhanced with the use of AI and
invading human errors. It is also revealed that
in prosthodontic implant applications benefit the
most from its success of prosthesis. In addition,
researchers were found to use AI to create
systems for dentistry and improve overall health.